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The European Council completed the legislative procedure to establish the Carbon Border Adjustment Mechanism (CBAM) on April 25, 2023, which will be launched in 2027. The iron and steel sector is the main target of the forthcoming CBAM due to the industry's energy-intensive consumption with high carbon dioxide (CO 2 ) emissions. However, minimal existing research has been conducted in this regard. This study employs GTAP-e 11.0 and TOPSIS models to estimate the effects of CBAM implementation on the major nations around the world from 2027 to 2030, examining countries' GDP, social welfare, iron and steel production, trade balance, and CO 2 emissions to the global environment. This study concludes: (1) The GDP and social welfare of important iron and steel trade partners throughout the world will be significantly impacted by the application of CBAM. Most nations, including those in the EU, will experience negative GDP effects, with China undergoing the most pronounced social welfare declines followed by India. In contrast, the EU27 will benefit the most in terms of social welfare, followed by the US, Japan, and Russia. (2) Iron and steel production will decrease in all countries outside the EU, but it will have a positive impact on the trade balance of most countries. (3) The CO 2 emissions of all countries except for the EU and Japan will decrease, with a positive impact on preventing carbon leakage in the international iron and steel trade. (4) Comprehensive analysis demonstrates that the EU will benefit the most, and China will suffer the most from CBAM application. Based on the above conclusions, this study proposes corresponding policy recommendations., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The study analyzes the impact of renewable energy investments (RENIV) on the environment in China. In doing so, the study uses sectoral carbon dioxide (CO 2 ) emissions as the environment indicator, considers RENIV as the explanatory variable, includes monthly data from 2004/1 to 2020/6, runs quantile on quantile regression approach as the fundamental model, and further performs quantile regression for the controlling. The study reveals that RENIV curb CO 2 emissions in all sectors at higher levels of sectoral CO 2 emissions. Also, RENIV have a varying impact based on quantiles and sectors. Moreover, the results are robust based on the alternative approach. Thus, RENIV have a significantly decreasing impact on sectoral CO 2 emissions in China. Accordingly, China policymakers should continue to focus on providing a decrease in energy and industrial sector CO 2 emissions as the highest emitting sectors., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The rapid development of the Internet has significantly impacted various socio-economic activities. Using Chinese Industrial Enterprise database and Industrial Enterprise Pollution database, this research examines the impact and mechanisms of Internet development on CO 2 emissions. The key findings are as follows: (1) Internet development has substantially reduced the CO 2 intensity of enterprises, and this conclusion remains robust even after performing a series of robustness analyses. (2) The major mechanisms responsible for the reduction in CO 2 emissions are productivity improvement, technological innovation, and energy structure adjustment. (3) The analysis of heterogeneity reveals that the effect of Internet development on CO 2 reduction is more pronounced in coastal areas, areas with a high share of secondary industry, low-carbon industries, clean industries, small-scale enterprises, and export enterprises. This study provides empirical evidence supporting China's "Internet+" strategy and its progress towards achieving the "Carbon Peaking and Carbon Neutrality Goals.", (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The BRICS nations-Brazil, Russia, India, China, and South Africa-have grown significantly in importance over the past few decades, playing a vital role in the development and growth of the global economy. This expansion has not been without cost, either, since these countries' concern over environmental deterioration has risen sharply. Both researchers and decision-makers have focused a lot of attention on the connection between economic growth and ecological sustainability. By using nonlinear autoregressive distributed lag (NARDL) approach, the complex relationships were analyzed between important economic indicators-such as gross domestic product (GDP), ecological innovations (EI), energy consumption (ENC), institutional performance (IP), and trade openness (TOP)-and their effect on carbon emissions and nitrous oxide emissions in the BRICS countries from 1990 to 2021, this study seeks to contribute to this important dialog. Principal component analysis is formed for technological innovations and institutional performance using six (ICT service exports as a percentage of service exports, computer communications as a percentage of commercial service exports, fixed telephone subscriptions per 100 people, internet users as a percentage of the population, number of patent applications, and R&D expenditures as a percentage of GDP) and twelve (government stability, investment profile, socioeconomic conditions, internal conflict, external conflict, military in politics, control of corruption, religious tensions, ethnic tensions, law and order, bureaucracy quality, and democratic accountability) distinct indicators, respectively. The results of nonlinear autoregressive distributed lag estimation show that increase in economic growth would increase carbon dioxide and nitrous oxide emissions. The positive and negative shocks in trade openness have positive and significant impact on carbon dioxide and nitrous oxide emissions in BRICS countries. Furthermore, the positive shock energy consumptions have positive and significant effect on Brazil and India when carbon dioxide and nitrous oxide emissions are used. However, EKC exists in BRICS countries when carbon dioxide and nitrous oxide emissions are used. According to long-term estimation, energy consumption and technological innovations in the BRICS countries show a strong and adverse link with nitrous oxide and a favorable relationship with carbon dioxide emissions. In the long run, environmental indicators are seen to have a major and unfavorable impact in BRICS nations. Finally, it is proposed that BRICS nations can assure environmental sustainability if they support creative activities, enhance their institutions, and support free trade policies., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

China Overseas Economic and Trade Cooperation Zone (COCZs) which as a platform for China's foreign investment and trade has a potential impact on CO 2 emissions, while strengthening bilateral investment and trade between China and the host countries. Since most of the COCZs are located in countries along the "Belt and Road," the purpose of this paper is to investigate the impact of COCZs on CO 2 emissions of the countries along the "Belt and Road" and the mechanism of this impact. We constructed a panel data of 63 countries along the "Belt and Road" from 2000 to 2020, and conducted an empirical study using the difference-in-difference (DID) model. Our research result show that COCZs can significantly increase the CO 2 emissions of the countries along the "Belt and Road." Then, we conduct a series of robustness tests and endogeneity test on the estimation results of the baseline model, and the results of the tests all support the conclusion reached by the baseline model. Our heterogeneity analysis reveals that the effect of COCZs on CO 2 emissions is more significant in Asian countries with lower national income or industrialization and higher country risk. Finally, we analyzed industrial value added and energy depletion as possible impact mechanisms, the results of mechanism model shows that COCZs can increase the industrial value added and then significantly increase CO 2 emissions, but energy depletion was not an efficient mechanism. Our paper provides a new insight into the impact of bilateral economic and trade cooperation zones on CO 2 emissions in host countries., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

China has abundant agricultural and forestry waste resources that are crucial sources of energy for substituting fossil fuels and achieving the carbon peaking and carbon neutrality goals. These resources play an essential role in reducing carbon dioxide emissions and promoting sustainable development. This paper presents an estimation of the number of biomass resources that can be used for energy in 2020 by using parameters such as the grass-to-grain ratio coefficient and excretion coefficient. Moreover, the potential for conversion of biomass resources into biomass energy is evaluated by using parameters such as lower heating value and gas production coefficient. Finally, based on the whole life cycle theory, the potential of biomass energy utilization to reduce carbon dioxide emissions and its impact on carbon peaking is calculated. It was found that the total amount of fossil fuels that can be replaced by biomass energy is 256 million tons of standard coal. Utilizing biomass energy can reduce carbon dioxide emissions by approximately 520 million tons, with a peak impact of 4-6% on carbon peaking. The research results presented in this article can provide valuable data to support the promotion of green transformation in various regions. The findings can serve as a useful reference for formulating localized biomass utilization plans and designing effective emission reduction policies., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The Belt and Road Initiative proposed by China has significantly increased trade in countries along the Belt and Road (B&R). Since most of these countries are developing and emerging economies, the pressure to reduce carbon emissions poses a leading challenge for them. Carbon productivity has become a key indicator for assessing the degree of low-carbon development, as it can link economic development with CO 2 emission reduction. However, few studies have investigated how international trade affects carbon productivity. Based on panel data from 43 countries along the B&R during 2001-2019, this paper uses a system GMM model to explore the impact of international trade on carbon productivity. Then, we divide the 43 countries in the sample into two groups according to their income levels to compare the different effects of international trade on carbon productivity. The results show that, first, the carbon productivity of the examined B&R countries has an overall increasing trend, and there is a significant heterogeneity of carbon productivity among countries with different income levels. Second, the effects of international trade, export, and import on carbon productivity are all significantly positive, and export's effect is higher than import. In the high-income group, carbon productivity is more likely to be improved by trade than in the middle (low)-income group. Third, economic development level, urbanization, and energy productivity are positively associated with carbon productivity, while CO 2 per capita and government size inhibit carbon productivity improvement. Insight into the impact of international trade on carbon productivity provides theoretical support for B&R countries to better leverage foreign trade activities to achieve a green economy., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Sustainable consumption is crucial in reducing the growing pressure of environmental crises. This study proposes the Technique of Order Preference by Similarity to the Ideal Solution (TOPSIS) approach to evaluate sustainable consumption toward green growth. The proposed approach assesses criteria weights in Interval Valued Neutrosophic Sets (IVNSs) using the Method of Maximizing Deviation. The proposed method evaluates sustainable consumption for ten selected developed and developing countries, including Canada, France, Japan, China, Indonesia, Korea, Malaysia, Singapore, Thailand, and Vietnam. The evaluation process encompasses four main criteria with eight sub-criteria, namely environment (population density, CO 2 ), energy (total natural resource rents, renewable electricity), economics (value added of agriculture, forestry, and fishing, GDP per capita), and health (fertility rate, mortality rate). The countries are ranked based on the relative closeness coefficient. The results reveal that two economic sub-criteria are pivotal in the sustainable consumption rankings. Canada emerges as the country with the highest degree of green growth, attributed to its extensive land area and potential for renewable energy. Based on the findings, this study proposes some policy implications for Vietnam, including balancing fertility and mortality rates and regulating economic growth and resource exploitation., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As reported at the 26th UN Climate Change Conference (COP26), worsening climate situation has led to frequent extreme weather events around the world. The main cause of climate change is carbon emissions from human activities. While realizing rapid economic development, China has become the world's largest energy consumer and carbon emitter. To achieve the goal of carbon neutrality by 2060, it should reasonably use natural resources (NR) and promote energy transition (ET). In this study based on panel data on 30 Chinese provinces from 2004 to 2020, second generation panel unit root tests were performed after validating slope heterogeneity and cross-sectional dependency. Mean group (MG) estimation and error correction model were used to empirically test the impact of natural resources and energy transition on CO 2 intensity (CI). The results show that natural resources exerted adverse effects on CI, whereas ET, economic growth and technological innovation were beneficial to CI. Analysis of heterogeneity indicates that natural resources exerted the greatest impact on CI in central China, followed by west China. Its impact in east China was positive but did not pass significance test. West China achieved the best result in carbon reduction through ET, followed by central China and east China. The robustness of the results was checked with augmented mean group (AMG) estimation. Our policy suggestions are to urge reasonable development and utilization of natural resources, accelerate ET to replace fossil fuels with renewable energy, and implement differentiated policies on natural resources and ET based on regional characteristics., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In recent years, environmental issues have become controversial, and policymakers are discovering new predictors of carbon emissions. Some economists/researchers have advocated for fiscal decentralization to improve the quality of the environment by offering more financial authority to provincial/local and sub-national governments. Therefore, this work aims to inspect the effect of fiscal decentralization on economic growth and environmental quality in India by taking data from 1996 to 2021. This work applies both ARDL and NARDL econometric models for empirical examination. The findings of this study suggest that expenditure decentralization has asymmetric long-term and short-term consequences on economic growth, and carbon emission in India. The result of the asymmetric ARDL model also indicates that positive and negative shock in expenditure decentralization contrarily affects economic growth and carbon emission. Moreover, the positive and negative shock in revenue decentralization helps in reducing carbon emissions both in the long run and short run in India. These outcomes are useful for policy analysis from the Indian economic policy perspective. The study also laid out potential outcomes that may benefit India's local governments and central government in resolving the issues of economic growth and environmental degradation., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

A key strategy for social development and sustainable urban expansion is building sustainable and affordable transport systems. In this study, we aim to test the validity of the environmental Kuznets curve (EKC) hypothesis and reveal the impact of infrastructure investment in transportation systems in China, Turkey, India, and Japan over the period 1995-2020 on environmental degradation. According to dynamic ordinary least squares (DOLS) method analysis, per capita GDP and per capita GDP 3 have a significant positive impact on per capita CO 2 emission, while per capita GDP 2 has a significant adverse impact on per capita CO 2 emission. These results confirm the validity of the N-shaped EKC assumption, while inconsistent with the results of the FMOLS technique, showing that per capita GDP is significantly positive, while per capita GDP 2 and per capita GDP 3 have a significant negative impact on per capita carbon emissions. Moreover, as clarified by the fully modified ordinary least squares (FMOLS) and DOLS methods, road infrastructure investment (RO), aviation infrastructure investment, trade openness, and foreign direct investment (FDI) have significant positive effects, while railway infrastructure investment (RA) has a significant negative effect on per capita carbon emission. Country-level estimates of per capita carbon emission-based DOLS strategies in the model show that only China and Japan have N-shaped EKC hypothesis. Road infrastructure investment, aviation infrastructure investment, and trade openness have significant positive effects, while railway infrastructure investment has a significant negative effect on per capita CO 2 emission in selected central and east Asian countries. The latest electrified rail systems are well thought out and less polluting, so the contribution of rail infrastructure investment to the transport mix can support sustainable and safe transport systems at city center and intercity levels and reduce environmental pollution in central and east Asian countries. Moreover, the implementation of the basic environmental settings of trade agreements should be strengthened to condense the growing impact of free trade on environmental pollution., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

With carbon emissions becoming more and more closely related to human activities and China being the world's largest emitter of carbon dioxide, the cost of environmental quality deterioration is high and environmental sustainability is low. Against this background, it is urgent to implement low-carbon recycling and green development by introducing green funds based on the role of environmental regulation intensity. Therefore, based on the data of 30 provinces from 2004 to 2019, the paper considers the dynamic impact of environmental regulation intensity and green finance development on regional environmental sustainability. The provincial data involve specific spatial locations and focus on the economic interactions among provinces, and the spatial econometric model is very applicable. Based on the spatial econometric model, this paper empirically examines the direct effect, spatial spillover effect, and total effect, considering both spatial and temporal patterns. The research shows that (1) China's provincial environmental sustainability shows a noticeable spatial agglomeration effect, which is significantly and spatially autocorrelated and clustered. (2) Based on the national level, an increase in the intensity of environmental regulation will significantly increase regional environmental sustainability, and the development of green finance will also significantly increase regional environmental sustainability. Additionally, the environmental regulation intensity has a significant positive spatial spillover effect, which may increase environmental sustainability in neighboring provinces. There is also a significant positive spatial spillover effect of the impact of green finance development on environmental sustainability. (3) Based on the provincial level, the impact of environmental regulation and green financial development on environmental sustainability in each region is significantly positive, with the most significant impact in the western region and the smallest coefficient in the eastern region. The paper proposes policy and managerial implications to promote regional environmental sustainability based on the above findings., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

China has announced a target of achieving carbon peaking by 2030 and carbon neutrality by 2060. Therefore, it is important to assess the economic impacts and emission reduction effects of China's low-carbon policies. In this paper, a multi-agent dynamic stochastic general equilibrium (DSGE) model is established. We analyze the effects of carbon tax and carbon cap-and-trade policies under both deterministic and stochastic conditions, as well as their ability to cope with stochastic shocks. We found that (1) from a deterministic perspective, these two policies have the same effect. Every 1% cut in CO 2 emissions will bring a 0.12% output loss, a 0.5% drop in demand for fossil fuels, and a 0.05% rise in demand for renewable energy; (2) from a stochastic perspective, effects of these two policies are different. This is mainly because economic uncertainty does not change the cost of CO 2 emissions under a carbon tax policy, but it does change the price of CO 2 quotas and the emission reduction behaviors under a carbon cap-and-trade policy; (3) from an economic volatility perspective, both two policies can act as automatic stabilizers. Compared to a carbon tax, a cap-and-trade policy can better ease economic fluctuations. The results of this study provide implications for policy-making., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper investigates the role of export quality in climate action goal of the sustainable development goals in emerging Asian countries. For this purpose, the empirical model that observes the impact of real GDP, energy use and export quality index on carbon emissions is constructed and is analyzed by ARDL bounds testing approach for the period from 1970 to 2014. We also include the square of real GDP as independent variable to observe the existence of environmental Kuznets curve (EKC) hypothesis which implies the parabolic relationship between economic growth and environmental degradation. The findings show that increase in export quality leads to a fall in CO 2 emissions for China and India. In contrast, the effect of increasing export quality increases CO 2 emissions in Thailand and the Philippines. Lastly, our asymmetric causality results show that the positive shocks of export quality causes positive shocks of CO 2 emissions in Thailand and Indonesia. Furthermore, we found that positive export quality shocks cause negative CO 2 emissions shocks in India while negative export quality shocks cause positive CO 2 emissions shocks in China. We also confirm the inverted U-shaped EKC hypothesis in China and Thailand., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Green growth refers to the economic growth strategy, which is less detrimental to natural assets, predominantly the environment. Therefore, the main motive of investment and innovation activities should be to attain economic growth while sustainably utilizing natural assets. In this regard, we aim to explore whether ICT diffusion and financial development matter for attaining green economic growth in BRICS economies. The long-run autoregressive distributed lag (ARDL) results show that internet development exerts a positive influence on green growth in four BRICS economies excluding India. However, the long-run estimates of mobile cellular subscriptions are positive only in Russia and China. On the other side, the increase in bank credit and insurance premium also contributes to the long-run green economic growth in almost all BRICS economies. Policymakers should focus on the increased use of ICT in the economy that would replace the physical resources in the economy with information resources. Besides, financial services should be provided to individuals and small and medium enterprises involved in green consumption and production activities., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study analyzes the effects of transportation infrastructure on carbon emissions (CE) based on the level of urban economic agglomeration. For this purpose, 281 Chinese cities are considered during the period 2003-2017. A Moran's I index is used to assess the spatial distribution characteristics of transportation infrastructure and CE. In addition, a spatial Durbin model is employed to explore the spatial spillover effect of transportation infrastructure on CE. Furthermore, economic agglomeration is considered as a crucial transmission mechanism. The empirical results show that (1) a significant spatial autocorrelation exists between transportation infrastructure and CE. (2) Transportation infrastructure significantly aggravates CE, with the "neighboring effect" being surprisingly more potent than the "local effect." (3) Economic agglomeration is a valid transmission channel through which transportation infrastructure affects CE, the intensity of which varies with the level of economic agglomeration. Our recommendation is that policy-makers should pay attention to the development of local transportation, as well as their neighboring cities, and should accelerate the advancement of green transportation., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Foreign direct investment (FDI) flows from developed to developing countries may increase carbon emissions in developing countries as developing countries are seen as pollution havens due to their lenient environmental regulations. On the other hand, FDI flows from the developed world may improve management practices and advanced technologies in developing countries, and an increase in FDI flows reduces carbon emissions. Most of the existing studies examine the relationship between FDI flows and carbon emissions by using aggregate FDI flows; however, this paper contributes to the literature by analyzing the impact of FDI flows on carbon emissions in Brazil, Russia, India, China, and South Africa (BRICS) between 1993 and 2012 using bilateral FDI flows from eleven OECD countries. According to our empirical results, from which OECD country FDI flows to BRICS countries matters for carbon emissions in BRICS countries. Our results confirm that FDI flows to BRICS countries from Denmark and the UK increase carbon emissions in BRICS countries, confirming the pollution haven hypothesis. On the other hand, FDI that flows from France, Germany, and Italy reduced carbon emissions in the BRICS countries, confirming the pollution halo effect. FDI flows from Austria, Finland, Japan, Netherlands, Portugal, and Switzerland have no significant impact on carbon emissions in BRICS countries. The BRICS countries should promote clean FDI flows by reducing environmental damages, and investing countries should be rated based on their environmental damage in the host countries., (© 2022. The Author(s).)

Climate action got attention from the United Nation's Sustainable Development Goals (SDGs). Although a large number of studies are investigating the said phenomenon, however, the literature on the top five responsible countries is unable to evaluate the role of environment-related technologies (ERTs) and institutional quality (IQ). The top five consumption-based carbon dioxide (CBCO 2 ) emitting economies, i.e., China, India, Japan, Russia, and the USA, are considerable stakeholders in this challenge. To fill this void, with the latest data available from 1992 to 2017, short- and long-run relationships are estimated with dynamic common correlated effects estimator and augmented mean group in the framework of EKC hypothesis. Reported results indicate the negative effect of ERTs and IQ towards CBCO 2 , which means that adoption of ERTs and better IQ is supportive in controlling environmental degradation. Findings are also robust to the policy implications for the UN's SDGs., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

International climate and green technology cooperation under the Belt and Road Initiative (B&R) have attracted significant attention, which led to several studies exploring B&R carbon emissions from the perspective of driving factors. While existing studies fail to consider the diversification of China's technology spillovers, the stochastic impacts by the STIRPAT and GWTR models are integrated in this study to determine the spatial impacts of three types of international technology spillovers (i.e., foreign direct investment (FDI), imports, and migrants) on the carbon emissions of B&R countries through independent innovations and technology following during 2003-2018. China's FDI and migration technology spillovers will increase B&R countries' CO 2 emissions through independent R&D and technology following, while imported technology spillovers will decrease B&R countries' carbon emissions through the same means. Therefore, this study shows that China's three technology spillovers show spatial differences in the CO 2 emissions of B&R countries. In short, government departments should formulate low-carbon technology policies according to the technology impact path and regional characteristics., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Low-carbon innovation plays an essential role in carbon reduction worldwide. This study investigates the nexus between low-carbon innovation, economic growth, and carbon emissions by the dynamic spatial Durbin model from 2007 to 2020. First, the Moran index results verify the provincial spatial agglomeration of carbon emissions. High-emission provinces concentrate in major economic zones and energy extraction areas. Second, the effect decomposition results show that long-term and short-term effects are consistent. Low-carbon innovation has a significant mitigation effect on carbon emissions in local regions, which effect, however, is not significant in the adjacent areas. The environmental Kuznets curve hypothesis is validated locally, but all provinces and cities have not reached the inflection point of the environmental Kuznets curve, and the linkage effect in adjacent regions remains insignificant. The above results have been tested to be robust. Third, the results of the mechanism analysis show that environmental policies, absorptive capacity, and financial development play a moderating role in the relationship between low-carbon innovation and carbon emissions. Finally, the heterogeneity test showed significant differences between Eastern, Central, and Western. The direct effect of low-carbon innovation exists in Eastern and central regions; the spillover effect of low-carbon innovation is only in the eastern region. In addition, corresponding measures are proposed based on the conclusions., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As an emerging driving factor, the positive impact of renewable energy technology innovation (RETI) on inclusive low-carbon development (ILCD) may be undervalued or even neglected. This paper develops an evaluation system to measure China's ILCD by using provincial panel data from 2006 to 2020. Based on the combined perspective of spatial spillover effect and threshold effect, this paper examines the spatial spillover effects and the regional boundary of RETI on ILCD in different periods and further analyzes five heterogeneities. The results show that (1) RETI and ILCD are increasing steadily, presenting a spatial pattern of "high in the east and low in the west." (2) Overall, RETI significantly promotes ILCD in local and neighboring areas. RETI in the growth period inhibits local ILCD, which in the mature period promotes local and neighboring ILCD. (3) The spatial spillover boundary of the whole RETI is 1400 km, that of RETI in the growth period is 1000 km, and that of RETI in the mature period is 1600 km. (4) The promotion effect of RETI on ILCD enhances over time and shows a spatial pattern of "eastern > central > south > north > western." It is further found that RETI strongly promotes ILCD in non-resource-based, high marketization, and strong environmental regulation areas. Therefore, it is necessary to break down administrative and market barriers, strengthen inter-regional cooperation and interconnection of resource elements, and establish a dynamic management mechanism of "one province, one policy" according to the regional heterogeneity for providing decision-making reference in promoting global energy transition and climate governance., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study aims to examine the effect of carbon dioxide emission and air pollution on agricultural productivity while accounting for the effect of renewable energy use, ICT, technological innovation, environmental policy stringency, and democracy for Brazil, Russia, India, China, and South Africa (BRICS) during the period 1990-2019. Several econometric procedures including mean group estimates are employed. The result suggests that both carbon dioxide emission and air pollution negatively affect the productivity of the agricultural sector. The effects of renewable energy, ICT, technological innovation, and democracy are found to be increasing agricultural productivity. Environmental policy stringency coefficient confirms the porter hypothesis. The result from the causality test suggests that bidirectional causality exists between CO 2 , PM 2.5 , renewable energy, technological innovation, ICT, and agricultural productivity. Finally, the study provides several policy suggestions for the governments of the BRICS economies in order to increase agricultural productivity while tackling the environmental vulnerability., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The popularity of green economy as an innovative technique and financial mechanism has soared as a result of this exchange, the gross domestic product (GDP); transition economy (TE); CO 2 emissions; human capital (HC); Government Fund Strategy (GFS); green finance (GF) play a very important role. When it comes to advancing genetic civilization, China's achievements in the field of green money have become firm proof of the country's progress. China has come to terms with the fact that it cannot continue on its current path of promoting monetary development at the expense of the environment, both for its own people and for the sake of the global community. The country has prioritized environmental concerns over equality with others through economic, political, social, and other factors. Furthermore, in order to accomplish the enormous goal, China's cross-country coal use must be covered to allow it to peak before 2020, and fossil fuel byproducts must peak before 2030. This article argues that China's "green drive" is a cause for optimism and concludes by arguing that the top 2030 goal for fossil fuel byproducts is ambitious but doable., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper investigates the impacts of new digital technology on carbon emissions in China. To better capture the feature of new digital technology, we distinctively measure it using the invention patent stock of new generation information technology industry. The empirical results show that the development of new digital technology significantly reduces carbon dioxide (CO 2 ) intensity. The results are still robust after addressing the endogeneity issues using instrumental variable regressions. The carbon reduction mechanisms of new digital technology include reducing energy intensity, optimizing energy structure, and advancing treatment technology. We further confirm the spatial spillover and nonlinear effects of new digital technology on CO 2 intensity and the moderating effect of urban digitalization in carbon reduction. The study suggests that the potential of new digital technology in reducing carbon emissions should be highly attentioned by governments., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study dynamically examines the impact of foreign direct investment and other explanatory variables on economic growth and carbon emissions, and tests the validity of pollution haven hypothesis (PHH) and environmental Kuznets curve (EKC) hypothesis in China, India, and Singapore from 1980 to 2020. The results of Westerlund's (Oxford Bulletin of Economics and Statistics, 69(6):709-748, 2007) panel cointegration test illustrate long-run equilibrium relationships among the proposed set of panel variables in the model. The estimated parameters of the AMG, CCEMG, and MG estimators in each of the specified models show that renewable and non-renewable energy consumption, foreign direct investment, and capital accumulation all have significant and progressive effects on economic growth. However, the labor force is insignificant and carbon emissions have a significant negative impact on economic growth. Non-renewable energy consumption significantly stimulates and renewable energy consumption significantly reduces carbon emissions. Moreover, the moderating role of non-renewable energy in the impact of foreign direct investment on carbon emissions is significantly positive, thus validating the PHH. The moderating role of renewable energy consumption in the impact of foreign direct investment on carbon emissions is significantly negative. The study's analysis also clearly validated the inverted U-shaped EKC hypothesis in China, India, and Singapore. Policymakers in emerging economies must prioritize the maturity of renewable energy, which not only increases productivity but also protects the environment from damage by reducing carbon dioxide emissions. The governments of China, India, and Singapore should initiate direct foreign inflows based on advanced and clean technologies to avoid environmental degradation and drive higher growth in these economies., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

China is currently in the process of the middle and late stage of industrialization, and energy-related CO 2 emissions have reached 10 Gt. This paper models energy consumption and related CO 2 emissions and analyzes the development trends of various driving factors of CO 2 emissions, explicitly considering China's economic and social development goals in the medium- and long-term. Different scenarios for 2020-2060 are projected based on the Kaya identity. Energy consumption will peak at 6,200 Mtce in 2035 in the BAU scenario with the energy-related CO 2 emissions peaking at 11.1 Gt in 2026-2027 advanced by the rising non-fossil energy share, while energy consumption and CO 2 emissions in the accelerated transition scenario would be potentially reduced by 300 Mtce and 300-400 Mt respectively. In the BAU scenario, the net CO 2 emissions will remain around 2,000 Mt in 2060, after removing 1,800 Mt by CCS/CCUS, indicating that China needs to enhance its post-2030 policy to deliver the carbon neutrality pledge. Steady energy efficiency improvement, radical industrial and energy restructuring are three key driving forces for carbon neutrality., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study aims to evaluate the environmental and employment impacts of China's value-added trade using the gross exports decomposition method and balance of avoided factor content. The major findings are that China's value-added trade overall leads to increases in global emissions and employment, which are mainly affected by the characteristics of China's exports. However, China's imports indirectly promote global emissions reductions and have a significant driving effect on foreign employment. Trade through onefold value chains plays a dominant role in determining both impacts. Simple global value chain (GVC)-related trade contributes most to reducing global emissions but decreases global employment as well. Complex GVC-related trade overall increases global employment and emissions. At the bilateral level, the impacts are varied, and there are some instances of complex GVC-related bilateral trade that contribute to global emission mitigation. A win-win situation for the environment and employment can be achieved in China's bilateral trade with some countries through specific value chain routes. These findings can provide useful information for balancing trade growth, carbon emission reduction, and job creation and may indicate the future direction of China's upgrade in the GVCs and help allocate emission reduction responsibilities., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In 2017, a carbon emissions trading market will be launched nationwide by the China government. Calculating the enterprise carbon emissions is an important prerequisite and basis for trading. This paper discussed types of greenhouse gases, calculation boundaries and methods, energy consumption, carbon emissions, and intensity of a representative integrated pulp and paper mill in China based on China Guidance and Greenhouse Gas Protocol Tools. The results showed that there were 435,000 tonnes (t) of CO2 emissions from that mill in 2014 that did not contain emissions of biomass energy, which was 8 times higher than that of fossil energy. The pulp carbon intensity based on the mill was 0.230 t CO2/Adt, which accounted for 7.50% to 57.4% in other pulps' based on the product. Intensity based on Gross Domestic Product (GDP) was 1.090 t CO2e/1000 USD and accounted for 56.8% intensity in the China paper industry. The intensity based on sales accounted for 52.6% in the firstclass enterprise in the developed country. It also showed that intensity was influenced by the species of raw material, energy, and products, which provided the mill with measures for energy saving and emissions reduction to obtain the redundant carbon emissions in the trading. [ABSTRACT FROM AUTHOR]

This study aims to investigate the impact of environmental technological innovations and environmental policy stringency on green economic growth in China. The empirical analysis of the study is based on the ARDL model. Findings confirm that environmental technology positively impacts green economic growth in the short and long run. In the robust model, the estimates of all technologies appeared to be significantly positive in the short and long run. Conversely, the estimated coefficients of environmental policy stringency, in the basic and robust model, have only negatively impacted the green economic growth in China in the short run. In the long run, the environmental policy stringency has not shown any significant impact on green economic growth in China in the basic and robust model. China needs to increase environmental technology and environmental policy stringency for achieving green growth and sustainability targets., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Green innovation undoubtedly plays a significant role in generating employment opportunities, improving green economic activity, and increasing environmental sustainability. This study scrutinizes the effect of energy efficiency and green innovation on CO2 emissions for China using nonlinear autoregressive distributed lag (NARDL) from 1991 to 2019. Findings show that energy efficiency and green innovation contribute to reducing CO2 emissions in China. Energy efficiency and green innovation are also important nonlinear determinants of CO2 emissions. An increase in energy efficiency and green innovation lowers CO2 emissions, while a fall in energy efficiency and green innovation increases CO2 emissions in China in the long run. Some policy measures are suggested to attain carbon neutrality., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study aims to analyze the asymmetric long-run relationship between economic growth (EG), foreign direct investment (FDI), and carbon emissions (CO 2 ) within the context of the environmental Kuznets curve (EKC) and the pollution haven hypothesis (PHH) in China. Employing the quarterly data from 1982Q1 to 2018Q4, we have used novel techniques to meet the stated objectives of our study, named quantile ARDL and quantile Granger causality. The study provides novel outcomes using the advanced quantile ARDL and quantile Granger causality tests. The significant implication of this method is that it provides locational asymmetry. We find strong evidence of the EKC and PHH for China based on the empirical results of linear and nonlinear ARDL models. Similarly, findings of quantile Granger causality validate the bidirectional relationship among all variables in upper and lower quantiles. Moreover, the results of the Wald test confirm the asymmetric long-run relationship between FDI and carbon emissions (CO 2 ). Thus, legal measures must be enhanced, accepted, rigorously imposed, and monitored in all provinces to assure a further reduction in carbon emissions. This study will be conducive for the policymakers to combat environmental contamination concerning economic growth and FDI inflow in China., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

China's Going Global Strategy and Belt and Road Initiative gained great attention among scholars. Moreover, it is believed that Chinese investments abroad cause serious social and environmental externalities. Hence, in this paper, we examine how China's foreign direct investments influence the carbon emissions of 35 Belt and Road Initiative countries from 2000 to 2019. To do so, we use a panel model that accounts for heterogeneity and country cross-section dependence. Our results show that while other countries' foreign direct investments have contributed to the deterioration of the environment in these countries, Chinese investments have not. This substantiates the hypothesis of the halo effect influence of China's foreign investments as opposed to other countries' investments which may seek a haven for its carbon emissions. These results highlight the importance of source and destination regulations of foreign direct investments in terms of their environmental impact and carbon emissions in the Belt and Road Initiative countries. It also provides a fresh finding on the efficacy of China's foreign investment management policies and regulations in producing the desired environmental outcome in hosting countries., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The carbon-reducing effects of artificial intelligence (AI) will be a critical means of achieving carbon peak and carbon neutrality in China. However, in order to efficiently harness the power of AI, the relationship between AI and carbon reduction needs to be fully understood. In this study, we systematically investigated the impacts and mechanisms of action of AI on CO 2 emissions by constructing econometric models using dynamic panel data from 30 provinces in mainland China from 2006 to 2019. The empirical results show that AI significantly reduces CO 2 emissions. Further mediation effect tests found that in the western region, there are mediation effects of the quantity and quality of industrial structure advancedization and industrial structure ecology, while the mediation effect of industrial structure rationalization is not significant. In the eastern and central regions, the mediating effect of the quantity of industrial structure advanced is not significant, while the mediating effect of the quality of industrial structure advanced, industrial structure rationalization, and industrial structure ecology all exist. Our work provides evidence to support that AI reduces CO2 emissions in various regions of China. This can help regions formulate appropriate policies to promote the synergistic development of AI and the "dual-carbon" goal., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The study was aimed at investigating the dynamic relationship between environmental taxes, green financing, and carbon dioxide (CO 2 ) emissions in Brazil, China, India, and South Africa from 1994 to 2019. To thoroughly examine the proposed relationship, a family of robust econometric methods is used to get reliable and accurate results. Our evidence indicates that green finance and CO 2 emissions are negatively connected with each other. Similarly, positive relationship is found between environmental taxes and CO 2 emissions. Additionally, environmental taxes and green finance are positively related as well. Further, the results of the Method of Moments Quantile Regression estimator indicate that green finance and CO 2 emissions decrease in countries with higher pollution compared to those with lower pollution. Interestingly, environmental taxes only contribute to pollution in countries with higher emissions, whereas CO 2 emissions increase environmental taxes in all sample countries. Lastly, green finance has a mitigating effect only in countries with greater pollution, and CO 2 emissions have a negative rebound effect on green finance in countries with greater CO 2 emissions. According to the evidence, green financing can be an effective tool for promoting environmental quality. By allocating the funds collected from environmental taxes to green financing, environmental sustainability can be promoted in sample countries., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper is a pioneer attempt using ecological footprints, the latest environment sensitivity proxy to be regressed, contributing to the scarce literature concerning one of the most burning global dilemmas of the era. For econometric analysis, fiscal and monetary tools, green energy consumption, and economic growth have been chosen as a set of regressors data spanning 1990-2020 in China facing the highest total ecological footpaths. And giving priority to the relevancy, reliability, and robustness autoregressive distributed lag (ARDL), fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) have been applied for instant and eternal sensitivities, followed by the widely used stationarity tests (augmented Dicky-Fuller and Phillips-Perron tests) and bounds test. Granger's ordeal has also noticed causal inferences. Cointegrating findings are robust across all techniques, and ARDL results remain consistent regardless of short and prolonged duration. We witness positive and statistically significant (at 10%) responsiveness of ecological footprints (EFP) to China's rapid gross domestic output (GDP) growth per capita fueled by fossil fuels (primarily coal). Contrarily, negative/inverse sensitivity to expansionary fiscal (higher government expenditures, GEx), contractionary monetary policies (higher policy rate, DR), and green energy use (REnC). Besides, EFP demonstrates statistically significant reciprocal interconnection with GDP and REnC but a unidirectional connection with DR (DR → EFP). GDP has effective collaboration with REnC and GEx whereas single-sided relationship DR as (GDP → DR). Finally, some policy choices are endorsed., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper aims to examine the nexus among carbon dioxide (CO 2 ) emissions, urbanization level and industrial structure in North China over the period 2004-2019, according to an expanded Cobb-Douglas production function. The panel econometric techniques are employed to complete the empirical analysis, including cross-sectional correlation test, panel unit root test, panel co-integration test, and panel Granger causality test. The empirical results support the long-term equilibrium relationship among CO 2 emissions, urbanization level and industrial structure in North China, and the urbanization level contributes most to CO 2 emissions, followed by fossil energy consumption. Furthermore, the bidirectional causality between CO 2 emissions and urbanization level and unidirectional causality from industrial structure to CO 2 emissions are found in North China, indicating that urbanization level and industrial structure have significant impacts on CO 2 emissions. Finally, according to the empirical findings, several policy suggestions are proposed for the purpose of reducing CO 2 emissions in North China., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Regional density is a useful tool for analyzing regional spatial structure as well as a good starting point for analyzing regional CO2 emissions per capita. This paper empirically analyzes the relationship between regional density and per capita CO 2 emissions in China's prefecture-level administrative regions. We improve the CO 2 emission measurement method for prefecture-level administrative regions and estimate the per capita CO 2 emissions of 252 prefectural-level cities in China from 2003 to 2013. Using panel fixed effect model regression, and taking the terrain roughness index as an instrumental variable to solve endogeneity, we find that the relationship between regional density and per capita CO 2 emissions presents in an inverted U-shape, per capita CO 2 emissions first increase with the increase of regional density, and after reaching the turning point, it decreases with regional density. In a mechanism test, analyzing the interaction terms between regional density and industrial structure, and regional density and urbanization level respectively. We found that industrial structure and urbanization are important mechanisms for regional density to affect CO 2 emissions. In order to reduce per capita CO 2 emissions, we propose corresponding policy implications for the regions in different positions of the "U" curve., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Environmental sustainability concerns are growing worldwide. Many recent studies have focused on key indicators of CO2 emissions, but less consideration has been given to human capital. This study examines the impact of human capital on CO2 emissions in Brazil, Russia, India, China, and South Africa (BRICS) economies from 1991 to 2019 using a nonlinear panel autoregressive distributed lag approach. Findings show that positive change in education has reduced CO2 emissions, while a negative change in education has increased CO2 emissions in the long run in a group of BRICS. Regarding economy-wise analysis, a positive change in education reduces CO2 emissions in Russia, China, and South Africa in the long run, but a negative change in education has an increasing impact on CO2 emissions in Brazil and China. The results of robustness are also maintained in group and economy-wise empirical analysis. Policymakers should develop the education sector infrastructure in order to support the decrease of CO2 emissions., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Exploring the low-carbon energy transformation pathway is vital to coordinate economic growth and environmental improvement for achieving China's carbon peak target. Three energy-target scenarios are developed in this paper, considering the targets of energy structure, electrification rate, and carbon mitigation towards 2030 announced by the Chinese government. A dynamic multi-sectoral computable general equilibrium model, CHINAGEM, is employed to examine the economic and environmental effects under different pathways of long-term low-carbon transformation. It detects that China's energy structure would substantially transfer to the low-carbon and clean one, whereas CO 2 , SO 2 , and NO X emissions in 2020-2030 would vastly abate along with all three energy-target scenarios. Different pathways would produce varying positive impacts on China's macro-economy and achieve the different extent of double dividend effects. It is highly conceivable for China to peak its carbon emission at 12.4 GtCO 2 by 2028 if it serves the comparatively more stringent low-carbon transformation pathways., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Against the backdrop of current global collaboration on mitigating carbon emissions, how to reduce the energy uses in the Belt and Road Initiative area becomes an urgent and big challenge facing the global community. Using the Eora input-output database, this paper accounts the embodied energy trade between Belt and Road countries in 2015, followed by an investigation of the factors influencing the embodied energy trade through a panel gravity model. Global value chain participation and position are two newly considered factors in analyzing the determinants of embodied energy flow. We find that the main bilateral embodied flow paths are from South Korea to China, China to South Korea, Singapore to China, Ukraine to Russia, and Malaysia to Singapore. Five percent embodied energy flow paths account for 80% of the total bilateral embodied energy flow volume between Belt and Road countries. The gravity model results indicate that gross domestic product (GDP) per capita, population, global value chain participation are the key drivers of bilateral embodied energy trade, while the industrial share of GDP and global value chain position are negatively related to the trade. Energy intensity plays a crucial role in reducing the bilateral embodied energy flow. These results are useful in the policymaking of sustainable development for the Belt and Road Initiative., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

We use input-output analysis and Levinson's structural decomposition method to measure China's CO 2 emissions under the no-trade hypothesis, to calculate how international trade affects China's emissions. We also analyze the driving factors of the difference between hypothetical no-trade CO 2 emissions and actual emissions and discuss the existence of "Pollution Haven Hypothesis" (PHH) in China. The results show that (1) from 2000 to 2017, the hypothetical no-trade CO 2 emissions are 2.43-14.67% lower than actual emissions. The scale effect is the main cause of this difference, while the composition effect fluctuates and has little impact. (2) Although exports make other economies' CO 2 emissions transfer to China, imports also help avoid China's emissions from some carbon-intensive sectors. (3) International trade has little impact on the cleanliness of China's industry composition. The no-trade industry composition is slightly cleaner than the actual one before 2010, after which trade improves the cleanliness of industry composition to a small extent. PHH is invalid for China in recent years, and results for most developing countries do not support PHH. (4) The relationship between no-trade effects and income per capita for all the economies does not also support PHH. Most economies reduce emissions, and their industry compositions are cleaner because of trade, regardless of their development degree. Trade will not severely influence China's future emission reduction, and improving the cleanliness of carbon-intensive sectors should be paid more attention to., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

More recently, the COVID-19 pandemic outbreak has created massive economic policy uncertainty (EPU). EPU and its economic fallout have been a hot topic of study; however, the impact of EPU on CO 2 emissions has been seldom addressed to date. This paper investigates the effects of the EPU on CO 2 emissions. It elucidates the role of EPU in moderating the environmental regulation-CO 2 emissions nexus at the national and regional levels using the panel data model and provincial panel data from 2003 to 2017 in China. The main empirical results are as follows. The EPU has a negative impact on carbon emissions; however, this relationship is non-significant even at the 10% level in the central and western region datasets. Environmental regulation positively increases the CO 2 emissions implying that the green paradox occurs in the whole and western regions datasets. From the perspective of the moderating effect of uncertainty, EPU exerts a positive impact upon the environmental regulation-CO 2 emissions nexus in the whole and western region datasets. The moderating effect is not significant in the eastern and central regions. The results demonstrate that the re-examination of the EKC hypothesis is inconclusive. Kuznets relationship between economic growth and CO 2 emissions for the national, eastern, and central samples was confirmed. In contrast, CO 2 emissions monotonically rise as GDP grows for western datasets. Based on the overall findings, some policy implications were put forward. We recommend that the local government should consider EPU to improve the institutional environment. Further, different regions should implement various environmental policies according to regional conditions maximizing the emission reduction potential., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The relationship between financial development and environmental sustainability has received significant attention in academic discourse. This study explores the crucial role of financial development in addressing the challenge of increasing CO 2 emissions. Using quantile-on-quantile and nonparametric causality-in-quantile methodologies, this research investigates the impacts and causal links between financial market and institution development and CO 2 emissions levels in five major polluting countries from 1990 to 2019. The findings provide strong evidence regarding the impact of financial institutions and financial market development on CO 2 emissions, demonstrating the presence of shocks and nonparametric causality from financial institutions and financial market development to CO 2 emissions quantiles. However, the effects of financial institution shocks and nonparametric causality are diverse and asymmetric across the sample. Positive and negative shocks are observed in India, while only negative shocks are observed in China, the USA, Russia, and Japan. Moreover, the findings reveal that the influence of financial market development on CO 2 emissions varies across countries, with both positive and negative shocks transmitted to CO 2 emissions in the USA, Russia, and Japan, indicating higher volatility in these countries compared to China and India, where only negative shocks are observed. Therefore, our recommendation emphasizes the prioritization of environmentally conscious financial products and the enhancement of the financial system's capacity to mitigate positive shocks contributing to increased CO 2 emissions. Implementing this strategy requires collective efforts to embrace sustainable financial practices that consider the environmental impact of financial activities., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Large-scaled interregional trade is based upon massive exchanges of natural resources, leading to more environmental emissions and economic imbalance. China is the largest trade country in the world and has to face such challenges since different Chinese provinces are in different development stages with different resource endowments. By using the latest multi-regional input-output (MRIO) tables and exergy accounting, this study aims to investigate natural resources and added values embodied in interregional trade in China for years of 2012, 2015, and 2017. Regional environmental inequality (REI) index and logarithmic mean Divisia index (LMDI) were applied to measure the imbalance states and uncover corresponding driving factors. Results show that the total trade volumes in the middle Yellow River and eastern coastal regions were generally higher than those in other regions, together accounting for 41.50 ~ 41.78% of the total trade volume during the study period. The major flows of embodied natural resources shifted from the middle Yellow River region to western coastal, eastern coastal, and southern coastal regions. The northern coastal and eastern coastal regions were the major exporters of embodied added value. Less developed regions had higher REI values, indicating more environmental and economic losses than developed regions. Natural resources intensity was the major impact factor on the trade imbalances in most provinces. This study provides valuable insights for alleviating trade imbalance and promoting sustainable natural resources management based on cross-regional collaboration., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As a major part of global development governance, G20 countries account for 80% of global carbon emissions. In order to achieve the goal of "carbon neutrality" proposed by the United Nations, it is important to compare and analyze the drivers of carbon emissions in G20 countries and provide recommendations for their carbon emission reduction. Based on the data of 17 G20 countries in the EORA database, this paper compares the drivers of carbon emissions of each country from 1990-2021 using weighted average structural decomposition and K-mean model. This paper focuses on four drivers, including carbon emission intensity, final demand structure, export structure, and production structure. Carbon emission intensity and final demand structure are the main factors of carbon emission reduction, and the other two factors have little influence. Among the G20 countries, the UK is in the first category because it does the best job on the four factors of carbon emissions, yet Italy is in the last category because it does not take full advantage of the four factors. Therefore, improving supply energy efficiency and adjusting demand, export, and industrial structure have become important tools for countries to transform and achieve carbon neutrality., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

European energy crisis, triggered by the conflict between Russia and Ukraine, has again drawn attention to the decarbonization of fossil energy sources. However, few studies have objectively considered coal from an integrated life cycle and its position in the energy system. In the present study, we used the integrated life cycle analysis and fixed-effect panel threshold model to reveal that (1) power generation and heating and iron and steel smelting are the highest CO 2 emission sectors. In addition, the coal chemical industry and power generation and heating are the two sectors with the highest contribution rate of CO 2 emissions. (2) Based on these, underground coal gasification (UCG) and underground coal gasification-integrated gasification combined cycle (UCG-IGCC) technologies were introduced to innovate the coal life cycle (the process cycle of coal production and utilization). The panel threshold model has proved that when the energy intensity falls in the interval 0.363-2.599, UCG-IGCC technology could be the complement in mitigating CO 2 emissions. (3) Finally, for the same amount of emission mitigations, the social cost of innovating coal production and utilization processes using UCG-IGCC technology will be lower than phasing out coal-fired power plants using carbon prices. For China, UCG-IGCC and renewable energy should be developed simultaneously., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Under the pressure of global carbon neutrality, it is necessary to study the characteristics of carbon emissions and the trend of "carbon peaking" in countries along the "Belt and Road." Because most of these countries have not yet reached their peak carbon emissions, they still have great potential for growth, and peak carbon emissions are a prerequisite for carbon neutrality. This paper divides the countries along the Belt and Road into 9 country groups according to the level of economic development and industrial structure. Based on the carbon emission panel data of countries along the "Belt and Road" from 1970 to 2018 and environmental Kuznets curve (EKC) theory, a panel model was established for each country group for research. This paper analyzes the characteristics of carbon emissions and the trend of "carbon peaking" in these countries and analyzes the economic growth and carbon emissions in combination with the Tapio decoupling model. The decoupling relationship changes on the time scale as a supplement. The results show that in the study area, some countries have completely passed the "carbon peak." The reasons for this are as follows: first, the carbon peak is achieved through industrial upgrading; second, the "carbon peak" is caused by the drastic changes in Eastern Europe and the disintegration of the Soviet Union and deindustrialization; and third, the carbon peak is caused by poverty and population growth. Most of the remaining countries have not yet achieved the carbon peak. Among them, some countries represented by the Middle East are highly coupled with their economic development and carbon emissions. Middle-income and high-industrial-dependence countries are in the transitional period in terms of the carbon peak. Low-income and medium- and high-industrial-dependence countries are currently still in the stage of barbaric development. From the research on the decoupling situation, the relationship between the economic growth of countries along the "Belt and Road" and their carbon emissions has been improving in recent decades, and it is expected that a more ideal state of decoupling will be achieved in the future., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study investigates the effect of financial development and economic growth on ecological footprint by including non-renewable energy consumption and trade openness as additional determinants. For this purpose, annual data of 10 countries with the highest ecological footprint (China, the USA, India, Japan, Brazil, Indonesia, Mexico, Korea, Turkey, and the UK) for the period 1992-2017 is used. The Westerlund and Edgerton (2007) Panel LM bootstrap test results reveal that there is cointegration between the variables. Additionally, the results obtained from the Common Correlated Effects (CCE) coefficient estimator show that financial development, economic growth, and non-renewable energy consumption negatively affect environmental quality by increasing ecological footprint. On other hand, the effect of trade openness on ecological footprint is found to be statistically insignificant. In addition, according to the panel causality test results, a unidirectional causality from financial development to ecological footprint is found while bidirectional causality between economic growth and ecological footprint exists. Therefore, it would be beneficial for policymakers in such countries to direct financial resources to green energy production and consumption and to encourage projects and practices., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

It is generally believed that fiscal decentralization is an essential way to increase the overall effectiveness and efficiency of the government through the transfer of financial autonomy to the local governments. On the same lines, this study attempts to confabulate the influence of two important economic indicators, (i) fiscal decentralization and (ii) natural resource rent in validation of the environmental Kuznets curve hypothesis. Our current analysis is grounded upon a developing economy - China - and will serve as a stepping stone for the similar economies. The time period for the empirical estimation is from 1990 to 2020. The study applied an advanced econometrics approach, called the quantile autoregressive distributed lag (QARDL), which has many advantages as compared to any conventional approach. The empirical outcomes, after estimations, illustrate that in the long run, FDE is having an unfavorable connotation with CO 2 emissions. NRR is another essential factor influencing the CO 2 emissions in the long run in the selected economy. The estimated outcomes are revealing the presence of the EKC. Furthermore, the present research elucidates the existence of the bi-directional causality between selected economic indicators, FDE and CO 2 emissions, and GDP square and CO 2 emissions. But there is a unidirectional causality between GDP and CO 2 emissions. Thus, policymakers should encourage the transfer of powers to the lower tiers of government to ameliorate environmental quality in the Chinese economy., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)