Uncovering the impact of income inequality and population aging on carbon emission efficiency: An empirical analysis of 139 countries

Unveiling the impact of aging on environmental sustainability in China: New insights from the Fourier ARDL approach

China is facing the dual challenges of rapid population aging and increasing environmental stress. Coordinating the relationship between demographic changes and environmental protection is a critical issue for China's sustainable development. Previous studies have primarily focused on carbon emissions or single pollutant indicators, overlooking the multidimensional nature of environmental stress and failing to fully consider the nonlinear relationships among variables. This study employs a more comprehensive load capacity factor (LCF) indicator and constructs a Fourier autoregressive distributed lag (Fourier ARDL) model, innovatively incorporating both nonlinear and periodic factors into the analysis. For the first time, this research systematically explores the nonlinear and cyclical interactions between population aging, economic growth, green technological innovation, and human capital, and their impacts on China's environmental sustainability. The results indicate that: (1) population aging, and economic growth exacerbate environmental stress, leading to a significant increase in LCF; (2) green technological innovation effectively alleviates environmental stress, having a significant negative impact on LCF; and (3) human capital has a dual effect on environmental sustainability, with a negative impact in the short term but a positive impact in the long term. Robustness checks further confirm these findings. This study suggests that China should proactively address population aging challenges, foster investment in green technological innovation, and prioritize the long-term accumulation of human capital to achieve sustainable development goals.

Analyzing the influence of financial technology and environmental taxation on energy transformation in BRI nations

This research examined the management, financial technology, and environmental taxation elements impacting energy transformation in Belt and Road Initiative (BRI) countries concerning foreign direct investment (FDI). The study aims to analyze data from 2014 to 2022, encompassing a balanced group of 148 BRI member nations-72 from minimal and lower-middle-class countries and 78 from significant and middle-income industrialized nations. Utilizing the two-step systems generalized method of moments (GMM) framework and verifying with the two-stage least squares (2SLS) approach, the study identified critical drivers and barriers to energy transformation in these countries. The findings indicate that effective management practices, advanced financial technologies, and appropriate environmental taxation policies significantly influence energy transformation and FDI inflows. Additionally, the research reviewed the impact of cruise tourism on human health and environmental ecosystems, highlighting severe environmental consequences such as habitat deterioration, marine pollution, and ecosystem disturbances. Human health issues linked to air and water pollution, including respiratory disorders and water-borne illnesses, were also identified. The socioeconomic effects on nearby communities were significant, underscoring the need for stringent regulations and sustainable practices. This comprehensive analysis provides essential insights for policymakers, industry stakeholders, and scholars, advocating for integrated policies to promote sustainable energy transformation and mitigate the adverse effects of cruise tourism.

Ensemble intelligence prediction algorithms and land use scenarios to measure carbon emissions of the Yangtze River Delta: A machine learning model based on Long Short-Term Memory

Land use in urban agglomerations is the main source of carbon emissions, and reducing them and improving land use efficiency are the keys to achieving sustainable development goals (SDGs). To advance the literature on densely populated cities and highly commercialized regions, this research evaluates the total-factor carbon emission efficiency index (TCEI) of 27 cities in China's Yangtze River Delta (YRD) urban agglomeration at different stages from 2011 to 2020 using two-stage dynamic data envelopment analysis (DEA). The study carries out regression analysis and a long-short-term memory model (LSTM) to respectively filter out the factors and predict TCEI. The results indicate the following. (1) The total efficiency of 27 cities has significantly improved from 2011 to 2020, and there are obvious spatial heterogeneity characteristics. (2) In terms of stages, most cities' efficiency values in the initial stage (energy consumption) exceed those in the second stage (sustainable land utilization). (3) In terms of influencing factors, urban green space's ability to capture carbon has a notably positive correlation with carbon emission efficiency. In contrast, the substantial carbon emissions resulting from human respiration are a negative factor affecting carbon emission efficiency. (4) Over the forthcoming six years, the efficiency value of land use TCEI in the YRD urban cluster is forecasted to range between 0.65 and 0.75. Those cities with the highest performance are projected to achieve an efficiency value of 0.9480. Lastly, this research investigates the interaction between actors and land resources on TCEI, resulting in a beneficial understanding for the former to make strategic adjustments during the urbanization process.

Digital economy development and carbon emission intensity-mechanisms and evidence from 72 countries

This paper employs two-way fixed effects models, mediation models and spatial panel models to examine the impact of digital economy development on carbon emission intensity in 72 countries from 2013 to 2020 using TIMG index as the proxy variable of digital economic development. The results of this paper show that (1) there is an inverted U-shaped relationship between the development of the digital economy and the carbon emissions in various countries. The development of digital economy first has a positive effect on carbon emissions, and then, its impact turns negative after it reaches a designated inflection point. (2) The results of the mechanism analysis show that the development of the digital economy can reduce carbon emissions by promoting industrial upgrading, while it could have an inverted U-shaped nonlinear effect on carbon emissions through energy efficiency. (3) The development of a country's digital economy may have a significantly inverted U-shaped spatial spillover effect on neighboring countries. This paper provides reference for countries to formulate carbon emission reduction policies and promote the coordinated development of digital economy and environmental protection.

Determinants of carbon emissions in Kenya and policy implications

Carbon dioxide emissions are the primary greenhouse gasses behind global climate change and its associated effects. Climate change adversely impacts the environment, biodiversity, and human health. The ability to tame carbon dioxide emissions will help in the fight against climate change. However, the recent pace of rising carbon dioxide emissions raises concerns about winning the war against climate change. World leaders are determined to take actions that will lower emissions. Thus, there is a worldwide effort to achieve net-zero emissions. Consequently, it is crucial to comprehend the specific factors that contribute to carbon emissions of specific economies so that countries can develop and enforce effective strategies for reducing carbon output, mitigating the effects of climate change, and improving recovery programs. Despite many empirical studies conducted in Africa on the determinants of carbon emissions, the results remain inconclusive and inadequate, leaving a void for further research. This study seeks to fill this knowledge gap by modeling the relationship between Kenya's carbon emissions (which have been increasing since the early 2000s), and mobile technology adoption, renewable energy mix, tourism development, development assistance, income, and global financial crises, utilizing the most current data from 1995 to 2021 from the World Bank's database. The ARDL, FMOLS, CCR, and DOLS analysis results reveal that mobile technology, tourism, development aid, and global financial crises increase Kenya's carbon emissions in the long run. At the same time, income and renewable energy reduce short- and long-term impacts. The significant insight from these results is that enhancing renewable energy development, mobile technology, and development assistance can promote a sustainable environment. From these findings, the study proposes many policy recommendations to help decision-makers, communities, companies, and the government in Kenya allocate resources and implement resilience and mitigation policies and programs in the areas most susceptible to the effects of climate change.

Assessing and gauging the carbon emission efficiency in China in accordance with the sustainable development goals

In light of the growing urgency of climate change, carbon emissions reduction has emerged as a pivotal concern within global governance. In this paper, we take carbon emission efficiency (CEE) as the research object to characterize the relationship between economic, social, and environmental development in the context of the Sustainable Development Goals (SDGs). According to the regional division standard of eight comprehensive economic zones in China, this paper analyzed the spatial differences, evolutionary characteristics, and influencing factors of CEE in 257 Chinese cities over the period 2003-2019. The analysis conducted the Dagum Gini Coefficient, Markov Transition Probability Matrix, and geographically and temporally weighted regression model (GTWR). The results demonstrate that: (1) The CEE of Chinese cities exhibits an upward trajectory. (2) The inter-differences among the eight comprehensive economic zones represent the primary spatial source of CEE divergence. (3) The CEE of Chinese cities is a staged process of gradual enhancement with spatial spillover effects. (4) Environmental regulation, energy consumption intensity, and green finances are significant factors affecting CEE, and the direction and intensity of their influence have distinct spatial heterogeneity. Ultimately, this paper proposes measures to narrow the development gap between regions and enhance the CEE across the region. Meanwhile, implementing regional refinement management and formulating differentiated regional sustainable development planning.

AI-enabled sports-system peer-to-peer energy exchange network for remote areas in the digital economy

In remote areas, particularly in developing countries, there is a growing interest in off-grid solar PV systems for their ability to provide clean and affordable electricity. However, these systems often face limitations in powering essential amenities, including sports facilities, due to restricted capabilities and inadequate battery storage. To address these challenges and promote energy independence, this paper proposes an AI-enabled sports-system peer-to-peer (P2P) energy exchange network within the digital economy. This innovative system leverages AI to optimize energy distribution specifically for sports-related infrastructures, ensuring efficient use of solar power and improved energy availability for both recreational and community needs. The proposed P2P network operates on a three-part Internet of Things (IoT) framework, facilitating automatic energy sharing among interconnected systems. This approach not only enhances the performance of existing solar power setups but also ensures that energy demands for sports facilities are met effectively. Feasibility studies of this system reveal promising outcomes, including a 13.67% increase in community energy independence and a 12.20% reduction in overall energy consumption. The AI-powered sports-system network demonstrates its potential to support sustainable development and improve the quality of life in remote areas by integrating sports and energy needs within the digital economy context.

Deep mitigation for trade-embodied carbon emissions among the Belt and Road Initiative countries

The frequent trade within and beyond the Belt and Road Initiative (BRI) has prospered the economy but has also expanded carbon emissions. Here, through a multi-regional environmental input-output analysis framework, we explore the patterns and inter-sectoral linkage of trade-embodied carbon emissions among BRI countries during 2015-2019. Then, a dynamic data envelopment analysis model considering carbon inequality as a non-discretionary input is constructed to assess the carbon emission efficiency of the identified key sector. We find that trade-embodied carbon emissions in the BRI steadily increased during 2015-2019. The manufacturing sector was identified as the key sector, exhibiting an overall efficiency of 0.6268 on average, with significant efficiency disparities. Moreover, we validate the positive role of efficiency enhancement in carbon emission mitigation, as well as the negative moderating effect of carbon inequality. Overall, this study provides optimal collaboration and initiatives to mitigate trade-embodied carbon emissions among BRI countries deeply.

Exploring online consumer behavior on fraudulent energy-saving products

Purchasing energy-saving products is key for public participation in energy conservation and sustainable development. However, the sale of fraudulent energy-saving products has boomed through online shopping, with little research on these products and consumer demands. This study explored the underlying factors driving consumer purchases of fraudulent energy-saving products and measured their impact on environmental awareness. Sales data for such products from four major online shopping platforms were collected. Results suggested unique demand characteristics from consumers who unknowingly purchase fraudulent energy-saving products, referred to as "hidden energy savers", including a preference for moderately priced products, a desire for straightforward energy-saving explanations, and a tendency to seek multiple additional features, even if they conflict with the core functionality. Perceived installation and usage difficulty significantly influences purchasing behavior. A practical survey of freight companies and individual transporters' demand for freight energy-saving products was conducted as a case study to validate the practical application of this research. This study presents a novel perspective on public energy-saving behavior, aiding in creating true energy-saving products, boosting public energy conservation interest, and reducing the negative impact of fraudulent products on environmental awareness. It also sheds light on hidden consumer needs, guiding the development of authentic energy-saving products.

Exploring dynamics relationship between carbon emissions and eco-environmental quality in Samarinda Metropolitan Area: A spatiotemporal approach

Carbon emissions have a negative impact on climate change. Environmental quality has faced significant challenges in the last decades. Eco-environmental quality helps assess the condition of the ecological environment to support humans' civilization and development. By using emissions raster dataset, remote sensing images, and LULC data, this study explores the status of carbon emissions (CE), eco-environmental quality (RSEICs), and the dynamic relationship between both variables in Samarinda Metropolitan Area, Indonesia. This study uses the spatiotemporal approach to deepen the understanding of CE-RSEICs during 2000-2021. The methods include the analysis of CE and the principal component of RSEICs. To understand the CE-RSEICs spatial features, the directional distribution ellipse method is used. Also, this study performs CE-RSEICs coupling analysis and identifies its LULC type composition. The findings show that CE status is still on an increasing trend, concentrating in the eastern region and keeping expanding during the period. The location of the low-emission ellipse is in the southwest, while the high-emission ellipse is in the east and intersects with the core cities. The mean RSEICs value is between 0.2878 to 0.4223, which indicates that the eco-environmental quality is categorized as fairly poor to inferior. Greenness, wetness, and Csink have a positive impact on RSEICs. The very poor-class ellipse is located in the inland region, and the very good-class ellipse is in the coastal area. The CE-RSEICs coupling status shows that the majority of the area has a weaker coupling degree. However, the higher coupling degree is concentrated in the population center and built-up region, which is the settlement area. The dominance composition of settlement area in higher coupling degree shows that settlement area has an impact on increasing CE-RSEICs coupling degree. So, sustainable low carbon development in coastal metropolitan area must continue to be carried out by considering CE-RSEICs and its spatial aspects.

Assessing energy consumption and economic growth interrelations in Asia-Pacific: A multivariate approach with panel FMOLS and bootstrap Granger causality tests

This study investigates the cointegration and causal relationship between energy consumption and economic growth using data from 16 Asian and Pacific countries from 1970 to 2010. The expanded production function is used in this investigation; this function considers not only labor but also financial resources. This study investigates whether or not a rise in energy demand is associated with a healthy economy. Human capital, in addition to material and labor resources, is taken into account by this operation. One of the first studies to adopt a multivariate method and add human capital was undertaken on the energy-growth nexus. Using the panel unit root and cointegration tests, this study confirms the existence of a long-run cointegrating connection between these variables. These studies recognize the presence of cross-sectional interdependence, according to specific reports. The significance of considering the interconnection of various countries is confirmed by comparing estimates from panel heterogeneous fully modified ordinary least squares (FMOLS) models with those from unceasingly efficient and fully modified models. Nonetheless, the bootstrap panel Granger causality test findings demonstrate that economic growth is a causal factor in rising energy consumption in the region, indicating that the relationship is not constant across countries.

How does regional economic integration affect carbon emission efficiency? Evidence from the Yangtze River Delta, China

Rapid urbanization and industrialization promote economic growth as well as bring carbon emissions, which seriously threaten the eco-environment and socioeconomic sustainable development. Facing increasing resource constraints, improving carbon emissions efficiency (CEE) is conducive to promote coordinated development of economy and environmental protection. In recent years, regional economic integration (REI) has rapidly developed. It can not only promote factors flow between regions but also achieve industrial and economic agglomeration. However, few studies have been reported in the literature about the relationship between the REI and CEE. In this study, we first illustrate how the REI influences CEE in theory, then take the Yangtze River Delta (YRD) as a case study to conduct empirical research. The results show that (1) the overall CEE value in the YRD has exhibited an upward trend from 2000 to 2020, and its spatial distribution has revealed a significant auto-correlation pattern. (2) On the whole, the REI act a noteworthy positive impact on CEE. When considering types of cities, it is found to have significant positive impacts for the CEE in economically developed cities, while it exhibits a negative impact in the less-developed ones. (3) Upgrading industrial structure and increasing per capita GDP can promote the CEE, but hinder its growth in surrounding areas. Our findings suggest that the government should formulate a unified overall plan to facilitate REI development and establish a modern industrial system of clean and low-carbon to promote regional sustainable development.

Renewable energy, inequality and environmental degradation

The connection between income inequality and environmental degradation remains a topic of persistent debate, marked by inconsistencies in both theoretical and empirical studies. This study offers a novel contribution to this discourse by investigating the simultaneous influences of renewable energy and income inequality on environmental degradation. Utilizing data from 158 nations from 2000 to 2017, our research reveals a crucial moderating role of renewable energy in the nexus between income inequality and environmental degradation. The study's key finding is that the impact of income inequality on environmental degradation is contingent on the level of renewable energy development. In scenarios with limited renewable energy, income equality leads to increased environmental degradation. However, when renewable energy is more developed, income equality contributes to reducing environmental degradation. This novel insight suggests that renewable energy development can mitigate the trade-off between pursuing income equality and environmental sustainability, thereby enabling their simultaneous achievement. The research also highlights that a more equitable income distribution enhances the environmental benefits of renewable energy. Further analysis demonstrates the significant role played by household consumption behavior and social norms in shaping this phenomenon. By adding these new dimensions to the existing literature, the study significantly enriches the understanding of the complex interplay among economic factors, renewable energy, and environmental sustainability.

Dynamic impact of demographic features, FDI, and technological innovations on ecological footprint: evidence from European emerging economies

Climate change effect mitigation is a critical priority for top leaders and communities around the globe. Human-induced environmental issues are affecting humankind's standard of living and development potential and the planetary boundaries. Sustainability objectives aim to enhance environmental quality and ensure sustainable development for all by eliminating social inequalities. This study examines the complex relationships between demographic features, foreign direct investment, technological innovation, and ecological footprint, emphasizing the relevance of population aging, population density, and urbanization in this context. The research uses a selection of emerging European economies during 1995-2018. The reasons for countries' selection are related to the increasing rate of population aging in European countries, the attractiveness for foreign direct investment, the economic growth, and the technological advancement potential these emerging countries possess. In order to investigate the long-run relationship between the selected variables, the study tests the cross-section dependence, homogeneity, and cointegration and uses Konya tests to determine panel causality. Based on Konya methodology, differences between countries in the panel are evidenced and discussed accordingly. Our findings confirm the long-run relationship between environment, technological innovation, population aging, and FDI. The results of this research are highly relevant for policymakers in selected countries for identifying the set of correlations and the relevance of various variables in such national economies. Demographic features such as population aging and population density are critical for Europe, and the results show the impact on the ecological footprint.

Impact of digitization on carbon productivity: an empirical analysis of 136 countries

Enhancing carbon productivity (CP) is key to achieving carbon reduction goals while maintaining economic growth. Digital technology plays a significant role in improving CP. Based on panel data from 136 countries worldwide from 2000 to 2020, this study empirically examines the impact of digitalization on CP and its mechanisms using fixed-effects and mediation models. The conclusions are as follows: (1) Overall, digitalization significantly enhances CP. (2) In terms of the mechanism, digitalization primarily improves CP through technological innovation and mitigating income inequality. (3) In terms of the quantile regression results, as the quantile level of CP increases, the promoting effect of digitalization on CP gradually strengthens. (4) From the perspective of heterogeneity among regions, income levels and human capital levels, digitalization has the greatest promotion effect on carbon productivity in European countries, high-income countries and high human capital countries. This study provides a reference for policymakers worldwide to use digital technology in achieving carbon emission reduction targets.

Foreign investments and load capacity factor in BRICS: the moderating role of environmental policy stringency

This research examines whether environmental regulations have a moderating effect on the link between foreign direct investment and the environment, as well as the effect of foreign capital investments on environmental quality for BRICS nations. In this approach, using second-generation panel data methodologies for the period 1992-2020, the impacts of foreign direct investments, real national income, consumption of renewable energy, and environmental stringency index on the load capacity factor are explored in the base empirical model. In order to test if there is any evidence of a potential parabolic link between economic growth and environmental quality, the model also includes the square of real national income. In addition, in the robustness model, the moderating role of environmental policy on foreign investment and environmental quality is checked. Empirical results show a U-shaped association between environmental quality and economic development. The usage of renewable energy and the environmental stringency index is also shown to improve environmental quality, although foreign direct investments decrease it. Finally, it is determined that environmental regulations are effective in undoing the negative impacts of foreign capital investments on environmental quality, demonstrating the validity of their moderating function.

Carbon neutrality endeavors: the impact of carbon emission trading policies on total factor carbon emission efficiency

Deepening the carbon market allocation reform is a strong support for carbon peaking and carbon neutrality. China has been piloting carbon trading in batches since 2013. However, there is little literature on whether and how carbon emission trading (CET) improves total factor carbon emission efficiency (TFCEE). To fill this gap, this study first calculates urban TFCEE using an extended Epsilon-based model and then designs a quasi-natural experiment based on causal inference. The staggered DID model is adopted to investigate the impact of CET pilot policies on urban TFCEE and its impact mechanism. Our results show that (1) the CET policy has a significant promoting effect on TFCEE in pilot cities, and this conclusion is reconfirmed by adopting robustness tests. (2) The mediating effect models are employed to confirm the mediating role of green technology innovation, industrial structure upgrading, and resource allocation efficiency in CET policy promoting regional TFCEE. (3) The heterogeneity test of CET policy depicts a considerable positive impact on TFCEE in cities with abundant resources. Eastern and developed cities are more likely to experience better carbon efficiency promotion through this policy than other cities. This study provides evidence for the important role of CET in promoting the development of a low-carbon economy and carbon neutrality.

The impact of population characteristics on transportation CO2 emissions-does population aging important?

Reducing transportation CO2 emissions and addressing population characteristic changes are two major challenges facing China, involving various requirements for sustainable economic development. Due to the interdependence of population characteristics and transportation, human activities have become a significant cause of the increase in greenhouse gas levels. Previous studies mainly focused on evaluating the relationship between one-dimensional or multi-dimensional demographic factors and CO2 emissions, while few studies have reported on the effect of multi-dimensional demographic factors on CO2 emissions in transportation. Analyzing the relationship between transportation CO2 emissions is the foundation and key to understanding and reducing overall CO2 emissions. Therefore, this paper used the STIRPAT model and panel data from 2000 to 2019 to investigate the effect of population characteristics on CO2 emissions of China's transportation sector, and further analyzed the effect mechanism and emission effect of population aging on transportation CO2 emissions. The results show that (1) population aging and population quality restrained CO2 emissions from transportation, but the negative effects of population aging were indirectly caused by economic growth and transportation demand. And with the aggravation of population aging, the influence on transport CO2 emissions changed and presented a U-shape. (2) Population living standard on transportation CO2 emissions exhibited an urban-rural difference, and urban living standard was predominant in transportation CO2 emissions. Additionally, population growth is under a weakly positive effect on transportation CO2 emissions. (3) At the regional level, the effect of population aging on transportation CO2 emissions showed regional differences. In the eastern region, the CO2 emission coefficient of transportation was 0.0378, but not significant. In central and western regions, the influence coefficient of transportation was 0.6539 and 0.2760, respectively. These findings indicated that policy makers should make relevant recommendations from the perspective of coordinating population policy and energy conservation and emission reduction policy in transportation.

Carbon intensity constraint, economic growth pressure and China's low-carbon development

Within the context of promotion tournaments among local governments, the management of economic growth goals plays a crucial role in China's economic development. Despite China's rise as the second-largest economy globally, it has also emerged as the largest emitter of carbon emissions. Since the implementation of the 12th Five-Year Plan in 2011, the Chinese central government has made carbon intensity targets mandatory indicators for national economic development. This has prompted local governments to pursue low-carbon growth and adjust their economic growth targets (EGT) to comply with carbon intensity constraints. In this study, a sample of 282 prefecture-level cities in China is used to empirically examine the impact of carbon intensity constraints on total factor carbon emission efficiency (TCE) using the intensity difference-in-differences (DID) framework. The study also emphasizes the role of the transmission channel for economic growth pressure (EGP). The findings of the study reveal several key results. Firstly, the implementation of carbon intensity constraints leads to an average increase of 8.24% in total factor carbon emission efficiency (TCE), which is supported by robustness tests, parallel trend analysis, and placebo tests. Secondly, these constraints result in an average decrease of 0.1828 in local governments' economic growth targets (EGT) and a reduction of 0.1269 in economic growth pressure (EGP). Thirdly, cities with a higher proportion of secondary industry experience a more significant mitigation effect, although the promotion of provincial EGT hinders this effect. Fourthly, synergistic policies can effectively promote low-carbon development, and government expenditure on technology and marketization can facilitate a positive relationship between carbon intensity constraints and TCE. Lastly, the effects of carbon intensity constraints vary across the east, middle, and west regions, suggesting the presence of heterogeneity. The article proposes a shift in the assessment of lower governments by superior governments, from growth assessment to low-carbon growth assessment.

Drivers and decoupling analysis of carbon emissions in the non-ferrous metal industry-evidence from 28 provinces in China

Emissions from the non-ferrous metal industry are a major source of carbon emissions in China. Understanding the decoupling of carbon emissions from the non-ferrous metal industry and its influencing factors is crucial for China to achieve its "double carbon" goal. Here, we applied the Tapio decoupling model to measure the decoupling status and developmental trends of carbon output and emissions of the non-ferrous metal industry in China. The panel interaction fixed effects model is used to empirically analyze the influencing factors of carbon emissions in China's non-ferrous metal industry. The results show that carbon emissions from China's non-ferrous metal industry have experienced three main states: strong decoupling, growth connection, and negative growth decoupling. The carbon emissions of the non-ferrous metal industry in some eastern and central provinces from 2000 to 2004 were in a negative decoupling state. Most provinces in the western and central regions were either in a strong or weak decoupling state based on the developmental trend of the decoupling state of carbon emissions. However, from 2015 to 2019, the decoupling status of carbon emissions in most provinces in western and central China had a significantly negative, weakly negative, or a negative growth decoupling status. Energy structure, energy intensity, cost, and non-ferrous metal production all have a positive driving effect on carbon emissions in the non-ferrous metal industry. Production had a mitigating effect on carbon emissions in the non-ferrous metal industry between 2010-2014 in the eastern region of China. From the results of our study, we propose policy recommendations to promote a strong decoupling of carbon emissions from the non-ferrous metal industry by improving energy structure, reducing energy intensity, and optimizing production capacity.

Assessing the spatial spillover effects and influencing factors of carbon emission efficiency: a case of three provinces in the middle reaches of the Yangtze River, China

Studying urban carbon emission efficiency is vital for promoting city collaboration in combating climate change. Prior research relied on traditional econometric models, lacking spatial spillover effects understanding at the urban scale. To provide a more comprehensive and visually insightful representation of the evolving characteristics of carbon emission efficiency and its spatial clustering effects and to establish a comprehensive set of indicators to explore the spatial spillover pathways of urban carbon emission efficiency, we conducted an analysis focusing on 42 cities in the middle reaches of the Yangtze River. By employing the index decomposition method, the super-efficiency SBM model, spatial autocorrelation analysis, and the spatial Durbin model, the study calculates the urban carbon emission efficiency from 2011 to 2019 and analyzes the spatial spillover effects and influencing factors of urban carbon emission efficiency. The main conclusions are as follows: (1) Jiangxi Province displayed stable urban carbon emission efficiency evolution, while Hubei and Hunan showed significant internal disparities. (2) Positive spatial correlation exists in urban carbon emission efficiency, with an imbalanced distribution. (3) Various factors influence urban carbon emission efficiency. Technological innovation and economic development have positive direct and indirect impacts, whereas industrial structure, urbanization, population, and energy consumption have negative effects. Spatial spillover effects of vegetation coverage are insignificant. These methods and findings offer insights for future research and policy formulation to promote regional sustainable development and carbon emission reduction.

Spatial and temporal evolution of urban carbon emission efficiency in China

Improving carbon emission efficiency is crucial for achieving carbon peak and carbon neutrality. This paper analyzes the carbon emission efficiency of Chinese cities using panel data from 275 prefecture-level cities between 2006 and 2020. The super-efficiency SBM (undesirable slacks-based measurement) model of undesired output, combined with kernel density estimation and exploratory data analysis, is employed. This study finds, firstly, from 2006 to 2020, the average efficiency of carbon emissions in Chinese cities declined from 0.53 to 0.48, indicating a downward trend. Secondly, from a temporal perspective, the level of dispersion in urban carbon emission efficiency has become increasingly distinct over time, coupled with a decrease in polarization. Thirdly, in terms of spatial analysis, urban carbon emission efficiency in China shows a positive correlation in a global context. In terms of local spatial correlation, it primarily exhibits high-high and low-low clusters, with a few instances of low-high and high-low clusters. Finally, based on the research findings, this paper proposes suggestions to improve urban carbon emission efficiency.

Impact of Internet development on carbon emission efficiency under carbon neutral target: evidence from global 58 economies

With the introduction of economy carbon neutral target policies one after another worldwide, the carbon emission reduction actions of economies around the world have become a hot topic attracting international attention. Meanwhile, the role of the Internet in energy saving and emissions reduction in economies around the world is also becoming more prominent. However, for now, there is still a lack of in-depth research on the impact and role relationship between Internet development and global economy carbon emission efficiency. Therefore, based on the availability of data, this study used the Malmquist index based on game intersection to measure and analyze carbon emission efficiency based on 58 economies around the world that proposed carbon neutrality targets between 2000 and 2019. The study used a spatial econometric model to explore the impact of Internet development on carbon emission efficiency. The objective was to provide a policy reference for high-, medium-, and low-income economies worldwide to achieve their carbon neutrality targets as soon as possible. The results of the study showed that carbon emission efficiency was closely linked to economic development level in economies around the world, that the gap between the development levels of high- and low-Internet-connected economies is gradually widening, that Internet development significantly improved carbon emission efficiency, that levels of economic and financial development played a mediating role in the relationship between Internet development and carbon emissions efficiency, and that the level of urbanization played a moderating role in the relationship between Internet development and carbon emissions efficiency. Exploring the influence and the mechanism of action between Internet development and carbon emission efficiency will contribute to early achievement of global carbon neutrality targets in all economies.

The impact of carbon emission trading policy on energy efficiency-evidence from China

Energy efficiency (EE) plays an important role in achieving the dual-carbon goal, and improving EE is thus indispensable. This paper evaluates the impact of carbon emission trading policy (CETP) on EE based on a difference-in-difference (DID) method, using 16-year data of 30 provinces and cities from 2005 to 2020. Conclusions are as follows: (1) CETP significantly promotes EE, and this conclusion still appears valid after robustness tests. (2) The positive impact of CETP on EE is more effective in regions of high foreign direct investment (FDI) and high government intervention (GOVI). (3) The positive impact of CETP on EE is through impact mechanisms of energy structure adjustment (ESA), green innovation (GI), and industrial structure upgrading (ISU). The findings in this paper may enrich current research in CETP and offer more pragmatic suggestions for policy advancement as well.

Spatial-temporal dynamics of land use carbon emissions and drivers in 20 urban agglomerations in China from 1990 to 2019

Urban agglomerations (UAs) are the largest carbon emitters; thus, the emissions must be controlled to achieve carbon peak and carbon neutrality. We use long time series land-use and energy consumption data to estimate the carbon emissions in UAs. The standard deviational ellipse (SDE) and spatial autocorrelation analysis are used to reveal the spatiotemporal evolution of carbon emissions, and the geodetector, geographically and temporally weighted regression (GTWR), and boosted regression trees (BRTs) are used to analyze the driving factors. The results show the following: (1) Construction land and forest land are the main carbon sources and sinks, accounting for 93% and 94% of the total carbon sources and sinks, respectively. (2) The total carbon emissions of different UAs differ substantially, showing a spatial pattern of high emissions in the east and north and low emissions in the west and south. The carbon emissions of all UAs increase over time, with faster growth in UAs with lower carbon emissions. (3) The center of gravity of carbon emissions shifts to the south (except for North China, where it shifts to the west), and carbon emissions in UAs show a positive spatial correlation, with a predominantly high-high and low-low spatial aggregation pattern. (4) Population, GDP, and the annual number of cabs are the main factors influencing carbon emissions in most UAs, whereas other factors show significant differences. Most exhibit an increasing trend over time in their impact on carbon emissions. In general, China still faces substantial challenges in achieving the dual carbon goal. The carbon control measures of different UAs should be targeted in terms of energy utilization, green and low-carbon production, and consumption modes to achieve the low-carbon and green development goals of the United Nations' sustainable cities and beautiful China's urban construction as soon as possible.

Links among population aging, economic globalization, per capita CO2 emission, and economic growth, evidence from East Asian countries

Population aging, economic globalization, and economic growth simultaneously cause changes in environmental quality, but so far no studies have integrated these key factors into the same environmental policy framework. Thus, this study uses the more robust Westerlund cointegration test and the augmented mean group (AMG) estimator (robust to cross-sectional dependence (CD), heterogeneity, and endogeneity) to estimate the long-term relationship between population aging, economic globalization, economic growth, and per capita carbon emissions in East Asian countries during the period 1975-2018. The analysis results reflect that population aging significantly reduces the long-term per capita carbon emissions of specific East Asian countries. However, energy generation and economic globalization make significant contributions to long-run per capita carbon emissions. Moreover, the impact of economic growth on long-term per capita carbon emissions is significantly positive, while the impact of square of economic growth on long-run per capita carbon emissions is significantly negative, thus validating the inverted U-shaped environmental Kuznets curve (EKC) hypothesis for specific East Asian countries. The results of the causality test indicated a two-way causality between energy generation and per capita carbon dioxide emission, supporting the feedback hypothesis. There is also a two-way causal relationship between aging population and per capita carbon dioxide emission. Policy recommendations are discussed in response to the empirical findings of this study.

The impact of industrial collaborative agglomeration on total factor carbon emission efficiency in China

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities.

Does renewable energy consumption improve environmental efficiency in 121 countries? A matter of income inequality

Renewable energy is a key component of the Sustainable Development Goals (SDGs) set by the United Nations, and is an important factor in facilitating the energy transition and carbon neutrality of countries. This study aims to examine the interaction between renewable energy consumption and carbon efficiency to achieve the goal of carbon reduction for environmental sustainability. This study measures the carbon efficiency globally and countries in each income group through the data envelopment analysis method. Then, this study empirically analyzes the impact of renewable energy consumption on carbon efficiency by controlling for heterogeneity, cross-sectional dependence and generalized moments estimation. The results show that (1) carbon efficiency enhances with the increase of income level, and the global carbon efficiency improvement is mainly due to the change of technological progress. (2) There is a weak improvement in scale efficiency in LI and LMI, dragged down by the decline in pure technical efficiency, which is the opposite of countries at higher income levels. (3) Renewable energy consumption has a positive effect on the improvement of carbon efficiency at all income levels, and there is a two-way causal relationship between renewable energy consumption and carbon efficiency. The effect of renewable energy on carbon efficiency is most significant in countries with middle income levels. Policy makers in each country should promote the renewable energy development to achieve energy transition and reduce carbon emissions. In addition, this study emphasizes that countries should consider the interaction between the renewable energy consumption and income level in ensuring sustainable development.

Decomposing the decoupling relationship between energy consumption and economic growth in China's agricultural sector

Sustainable food supply is affected by high energy consumption and negative environmental effects. Regarding the national strategy of "carbon peaking and carbon neutrality targets", the decoupling between energy consumption and economic growth in China's agriculture has received significant attention. Therefore, this study first presents a descriptive analysis of the energy consumption in China's agricultural sector from 2000 to 2019, before analyzing the decoupling state between energy consumption and agricultural economic growth at the national and provincial levels using the Tapio decoupling index. Finally, the logarithmic mean divisia index method is used to decompose the decoupling driving factors. The study draws the following conclusions: (1) At the national level, the decoupling of agricultural energy consumption from economic growth fluctuates among expansive negative decoupling, expansive coupling, and weak decoupling, before stabilizing in the last state. (2) The decoupling process also differs by geographic region. Strong negative decoupling is found in North and East China, and strong decoupling lasts longer in Southwest and Northwest China. (3) The factors driving decoupling are similar at both the levels. The economic activity effect promotes the decoupling of energy consumption. The industrial structure and energy intensity effects are the two main suppressive factors, whereas the population and energy structure effects have relatively weaker impacts. Therefore, based on the empirical results, this study provides evidence for regional governments to formulate policies on the relationship between the agricultural economy and energy management from the perspective of effect driven policies.

The drivers of carbon emissions in China: the perspective of fiscal decentralization

Fiscal decentralization determines government behavior considerably by being a major factor influencing China's carbon emissions. We analyze the impact of fiscal decentralization on carbon emissions on basis of the dataset of 30 Chinese areas for the period 2008 to 2020. We reveal that fiscal decentralization significantly raises carbon emissions, but worsens carbon emission efficiency. The impact of fiscal decentralization on carbon emissions varies significantly by geographical location and economic development level shocks. Local governments increase the expenditure on economic services while reducing the expenditure on basic public services as a result of the fiscal decentralization scheme, which is an important reason why the carbon emission level cannot be effectively improved. As such, it is necessary to keep pace with the times, and build a service-oriented government, and capitalize on the capabilities of local governments in terms of their service duties so as to maximize carbon reduction.

How does technological innovation affect carbon emission efficiency in the Yellow River Economic Belt: the moderating role of government support and marketization

The Yellow River Economic Belt (YREB) is a fundamental ecological protection barrier for China. Its carbon pollution issues are currently severe owing to the extensive energy consumption and unsatisfactory industrial constructions. In this context, this paper estimates carbon emission efficiency (CEE) based on the panel data from 56 cities in the YREB during the period 2006-2019 and analyzes its spatial distribution characteristics. Additionally, the spatial Durbin model (SDM) is utilized to examine the effect of technological innovation (TI) on CEE as a result of the moderating effects of government support (GS) and marketization (MA), respectively. The results indicated that (i) in the YREB, CEE exhibited significant spatial autocorrelation characteristics; (ii) TI negatively affected local CEE; (iii) the moderating effect of local GS on the relationship between TI and CEE in the local area was negative, but its spatial spillover effect was still not significant; (iv) the moderating effect of local MA on the relationship between TI and CEE in the local area was also negative, but positive in the surrounding areas. Based on the empirical analysis, a series of policy suggestions are proposed to improve the YREB's CEE.

Investigating asymmetric impacts of total factor energy efficiency on carbon emissions in India

As many complex energy relations are not linear and have diminishing returns, assuming a symmetric (linear) effect of energy efficiency (ENEF) on carbon emissions (CAE) has limited our understanding of the emission-ENEF nexus. This research, therefore, initially estimates total factor energy efficiency by applying a stochastic frontier technique using sample panels for India encompassing the period from 2000 to 2014. Further, a nonlinear panel autoregressive distributed lag modelling framework is utilised in order to investigate the asymmetric (nonlinear) long- and short-run impacts of ENEF on CAE. The findings demonstrated that ENEF has asymmetric long- and short-run impacts on CAE in India. Based on the outcomes, numerous crucial implications are discussed with a particular reference to developing economies like India.

Spatial characteristics and coupling coordination between carbon emission efficiency and industrial structure in three metropolitan areas of Jiangsu Province, China

It is of great practical significance to study the spatial characteristics of carbon emission efficiency, industrial structure, their coupling and coordination relationship for China's green development and industrial structure transformation in the new era. From the perspective of coupling, coordination and space, this paper analyzes and summarizes the spatial characteristics of carbon emission efficiency and industrial structure of 19 cities in three metropolitan areas of Jiangsu Province during 2009-2019 and their coupling and coordination relationship. The carbon emission efficiency in this study is represented by the carbon emission economic efficiency index and carbon emission social efficiency index. The results show that (a) the high-emission centers in the three metropolitan areas developed from "three centers" in 2009 to "five centers" in 2019. The continuous high-energy consumption of the secondary industry and the growth of the economic aggregate of the third industry kept the regional high carbon dioxide emissions. (b) The average value of carbon emission economic efficiency in 19 cities continued to increase, indicating that the contribution rate of the same amount of carbon emissions to economic income gradually increased; the growth range of carbon emission economic efficiency index is greater than that of carbon emission social efficiency index, indicating that carbon emission has a more significant effect on the improvement of regional economic development than on the improvement of public service level and residents' living quality. (d) The solidification degree of carbon emission efficiency is greater than that of the industrial structure (solidification degree carbon emission social efficiency > carbon emission economic efficiency > industrial structure). The high-grade industrial structure in Xuzhou metropolitan area is closely related to the improvement of carbon emission economic efficiency and carbon emission social efficiency, and both are in moderate antagonism. The rationalizing industrial structure in Nanjing metropolitan area is closely related to the improvement of carbon emission economic efficiency, which is in high coordination run-in. The concentration degree of industrial structure in Suzhou-Wuxi-Changzhou metropolitan area is closely related to the improvement of carbon emission economic efficiency and carbon emission social efficiency, which are in polar coordination coupling and high coordination run-in, respectively. The proposed coupling path of carbon emission efficiency-industrial structure can not only alleviate the dynamic disharmony in different cities but also effectively improve the coupling degree in cities.

Exploring the role of nuclear energy in the energy transition: A comparative perspective of the effects of coal, oil, natural gas, renewable energy, and nuclear power on economic growth and carbon emissions

Nuclear power has received renewed attention during the energy transition in recent years. This study is aimed to explore whether nuclear energy can promote economic growth without increasing carbon emissions. In order to have a more comprehensive understanding of the relationship between nuclear energy, economic growth, and carbon emissions, this study also discusses the impact of coal, oil, natural gas, and renewable energy on economic growth and carbon emissions. The second-generation panel unit root test, panel cointegration test, panel fully modified ordinary least squares, and Heterogeneous Dumitrescu and Hurlin causality test were used to estimate the long-term elasticity and causality among variables. Results based on panel data from 24 countries with nuclear energy from 2001 to 2020 show that both nuclear energy and renewable energy can curb carbon emissions. Especially in Canada, Finland, Russia, Slovenia, South Korea, and The United Kingdom, nuclear energy reduces carbon emissions more significantly than renewable energy. Meanwhile, there is a positive relationship between increased nuclear energy, increased renewable energy, and economic growth, which means that nuclear energy and renewable energy could increase economic growth as well. There is a positive relationship between increased oil, increased natural gas, and economic growth, while there is a negative relationship between the increase in coal and economic growth. Meanwhile, there is a positive relationship between increased oil, increased coal, and increased carbon emissions, while the positive relationship between increased natural gas and increased carbon emissions is not significant. Thus, in the 22 countries with nuclear power, increased coal consumption does not drive economic growth but increases carbon emissions. Increased oil consumption increases economic growth, but it increases carbon emissions. Increased natural gas consumption boosts economic growth but adds little to carbon emissions. In the authors' view, nuclear power and renewable energy are all options for these nuclear-power countries to pursue economic growth without increasing carbon emissions. Moreover, nuclear power has a better effect on curbing carbon emissions in some countries than renewable energy. Therefore, under the premise of safety, nuclear power should be seriously considered and re-developed.

Revisiting renewable energy and economic growth-Does trade openness a matter?

A significant obstacle to the scaling of renewable energy is the concern that increased consumption of renewable energy could have a negative impact on economic growth, due to the higher cost of renewable energy compared to fossil energy. To examine how exactly renewable energy consumption impacts economic growth, this study uses a non-linear panel threshold model with trade openness, financial development, and per capita income as threshold variables, to analyze the long-term non-linear relationship between renewable energy consumption and economic growth in 28 European Union countries from 2007 to 2017. The results show that (i) renewable energy consumption has significant threshold effect on economic growth. First, the effect of renewable energy consumption on economic growth is positive and significant if and only if it surpasses a certain threshold of trade openness. Second, a moderate financial development interval makes the consumption of renewable energy have a positive effect on economic growth, and if it is too low or too high, it will have a negative effect. Third, as for income level, the promoting effect of renewable energy consumption on economic growth is showing a "stepwise growth" feature, which means, when the income level surpasses its threshold value, the positive effect is strengthened. (ii) The results of the fixed-effects model show that, overall, renewable energy consumption promotes economic growth. (iii) The changes in the number of countries in different threshold intervals indicate that the positive impact of renewable energy consumption on economic growth in the EU is increasing.

Does environmental regulation improve marine carbon efficiency? The role of marine industrial structure

With the continuous increase of marine development, intensive economic activities have reduced the marine carbon efficiency and seriously damaged the marine ecological environment, which needs reasonable environmental regulations to guide. This study aims to examine the interactions between marine environmental regulation and carbon efficiency to achieve the goal of carbon emission reduction for the sustainability of marine ecosystem. This study empirically analyzes the heterogeneous effects and mediating effects of China's marine environmental policies on marine carbon efficiency using the mediating effects model and generalized moments estimation. The results show that there is a "U" shaped relationship between marine environmental regulation and marine carbon efficiency in China, marine environmental regulation can indirectly promote marine carbon efficiency through the transmission mechanism of resource allocation efficiency and structural optimization of marine industries. In addition, China's marine environmental regulation policies have regional heterogeneous effects on marine carbon efficiency. This study provides a new perspective for optimizing marine carbon efficiency and sustainable development of marine ecosystem.

Revisiting the environmental kuznets curve hypothesis in 208 counties: The roles of trade openness, human capital, renewable energy and natural resource rent

Achieving carbon neutral requires a comprehensive understanding of the effect of different key factors on carbon emissions. To this end, this study investigates the effect of trade openness, human capital, renewable energy and natural resource rent on carbon emissions within the framework of the environmental Kuznets curve (EKC) hypothesis. Second-generation econometric tests, Generalized Method of Moments and Fully Modified Ordinary Least Squares estimator were developed based on the aggregated dataset of 208 countries from 1990 to 2018. The results show that (i) the EKC hypothesis is validated when the effects of trade openness, human capital, renewable energy consumption, and natural resource rents are considered. The relationship between income level and carbon emissions shows an "inverted U-shaped" curve at the global level. Besides, the real GDP per capita corresponding to the EKC turning point is 19,203$. (ii) Renewable energy consumption and human capital have heterogeneous effects on carbon emissions in before- and after-EKC turning points. Specifically, renewable energy consumption has a better emission reduction effect for countries before the EKC turning point, with effects of -0.4334 and -0.1598, respectively; human capital has a better emission reduction effect for countries after the EKC turning point, with effects of -0.6311 and -0.3398, respectively.(iii) the mitigation effect of trade openness on carbon emissions is only effective in countries with weak decoupling after EKC turning points, with a mitigating effect of -0.0615. However, natural resource rents increase carbon emissions in most countries.