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The transportation industry (TRAI) is an important source of carbon emissions for China to achieve its peak carbon and carbon neutrality targets. This study analyzes the coupled integration of TRAI economic growth and carbon emissions in 30 Chinese provinces from 2005 to 2020 using a Tapio decoupling elasticity model and an environmental Kuznets curve (EKC) model. Then, a long-term energy alternative planning (LEAP) system model was constructed to predict and simulate the development of TRAI in China. The results of the study are as follows. (1) TRAI shows an inverted U-shaped decoupling in most provinces across the country, and most of the decoupling is usually more volatile in provinces with higher levels of economic development. In addition, COVID-19 positively contributes to the development of TRAI nationwide and in three regions. (2) The Tapio-EKC coupling curves of TRAI and eastern TRAI (ETRAI) nationwide have an inverted N-shape, and central TRAI (CTRAI) and western TRAI (WTRAI) have an inverted U-shape. Twenty-seven provinces crossed the decoupling elasticity inflection point nationwide, all provinces of ETRAI crossed the EKC inflection point, while all provinces of CTRAI and WTRAI did not cross the EKC inflection point; (3) The carbon reduction rates after scenario simulation ranged from 5.07 to 54.94%, with aircraft, ships, private vehicles, and their fuels (aviation kerosene, diesel, and gasoline) being the focus of energy saving and emission reduction. The coupled Tapio-EKC analysis model of this study is universal and can be extended to other provinces, cities, or industries. [ABSTRACT FROM AUTHOR]

Raising economic growth is the primary concern of most of countries especially the developing and emerging economies in order to enhance the living standard of people. However, increase in economic activities increases energy demand which rise carbon dioxide emissions and leads to environmental degradation. Technological innovations might be the remedy to overcome the issue of increased carbon dioxide emission by reducing energy use, raise energy efficiency and also push economic growth activities efficiently. In this regard, this study explores the interrelationship of technological innovation, carbon dioxide emissions, and economic growth from 1985 to 2019 in 35 Belt and Road countries. The study uses ordinary least squares, two-step system generalized method of moments, two-step difference generalized method of moments, seemingly unrelated regression, and three-stage least square models for analysis. The results indicate that technological innovations increase economic growth and enhance environmental quality. Foreign direct investment also increases economic growth while degrading environmental quality. Economic growth increases technological innovation while exerting harmful effects on the quality of the environment. The impact of trade on economic growth is positive, while financial development reduces economic growth. School enrollment has a significant and positive effect and increases technological innovation, while foreign direct investment and research and development reduce it. The results also confirm that research and development expenditures significantly reduce carbon emissions and enhance environmental quality. The findings of this study have considerable policy implications for the sample countries with respect to economic growth, technological innovations, and environmental quality. [ABSTRACT FROM AUTHOR]

Health and the environment are complex components of the countries, influenced by several factors, especially transport, and economics. Thus, this paper assesses the role of transportation and economic complexity in the environment and public health for the Organization for Economic Co-operation Development (OECD) countries from 2001 to 2020. This study also focuses on the relationship between transport and economic complexity with environmental and healthcare expenditures. Precisely, transport and economic activities stimulate healthcare expenditures through multiple channels. The current study employs the STIRPAT model to investigate the association with transportation, economic complexity, transport–carbon intensity, and healthcare expenditure. Besides, the current research confirms the plausible cross-sectional dependency across countries, and it adopts a second-generation technique. Analytical findings suggest that transportation-carbon intensity is positively and significantly associated with healthcare expenditures. Healthcare and transport–household expenditures increase transport–carbon intensity (TCI) by 75% and 45%, respectively, in the long run. In the contrast, TCI and transport–household expenditures have also a remarkable impact on healthcare expenditures and are estimated approximately 95% in the long run. Moreover, economic growth also upsurges TCI and healthcare expenditures through multiple economic activities. Besides, transport–household expenditures (THE) drastically impact transport–carbon intensity and healthcare expenditures (HEX) through passenger traffic (PTF). Diagnostic upshots unveil that the joint effect of THE and PTF increases TCI and HEX by 4 and 3%, respectively. Finally, findings recommend some policy implications and future research directions for the countries based on empirical outcomes. Countries should regulate economic activities to reduce transport carbon emissions. [ABSTRACT FROM AUTHOR]

In today's highly advanced industrialised and modernised world, China's economy is still growing, and its demand for energy is increasing daily. It is crucial to examine the connection between energy consumption, carbon emissions, and economic growth in order to promote economic growth based on energy conservation and emission reduction. Using Dezhou City in Shandong Province as an example, the study builds a VAR model of carbon emission, energy consumption, and economic growth in Dezhou City based on simplified macroeconomic sub-models, energy sub-models, and environmental sub-models. It then determines the correlation and influence mechanism between the three using tests like ADF unit root and Granger causality. The pertinent elements affecting Dezhou's carbon emissions were then investigated using grey correlation analysis. Finally, based on the study's findings, policy suggestions are made regarding energy use, carbon emissions, and economic expansion. It is necessary not only to restrain high-energy consumption industries and fundamentally optimize the energy consumption structure, but also to find new economic growth points and improve economic growth channels, so as to optimize the industrial structure. In this process, increasing the proportion of the tertiary industry is a key measure. In addition, the government needs to advocate the citizens to adopt a low-carbon lifestyle, and the concept of low-carbon environmental protection will be deeply rooted in the hearts of the people. This study will provide suggestions and theoretical guidance for China's energy consumption and carbon emissions, and help achieve high-quality growth of China and even the world economy. [ABSTRACT FROM AUTHOR]

Bangladesh, being the fastest growing economy in the South Asian region, necessitates a comprehensive study to evaluate the influence of various socio-economic factors. The primary objective of this study is to get a comprehensive understanding of the concept of sustainable development and its relationship to carbon emissions. This analysis will specifically consider the current status of economic and anthropogenic activities within the context of Bangladesh. This research examines the aforementioned matter by utilizing the latest accessible yearly data spanning from 1990 to 2020, as well as employing advanced econometric models including the dynamic autoregressive distributed lag approach and frequency domain causality test. The analysis of empirical data reveals that the economic growth experienced in Bangladesh has yielded a discernible and favorable influence on the degradation of the environment, in both the immediate and extended periods. Nevertheless, it is crucial to acknowledge that the observed impact holds no statistical significance. Furthermore, it is apparent that energy consumption has a substantial impact on the escalation of carbon emissions, in both the immediate and prolonged periods. Additionally, the processes of industrialization and foreign direct investment have also exerted adverse effects on short-term carbon emissions. A frequency domain causality test is used in this work to do a robustness analysis and confirm that there are causal links between economic growth, energy use, development, and carbon emissions over a range of time frames, such as the short, middle, and long terms. The above studies have given us a lot of useful information about how economic growth, energy use, industrialization, and environmental sustainability all affect each other in Bangladesh. Bangladesh should prioritize the formulation of policies and regulations that are centered around specific goals. These objectives include: (a) enhancing government engagement in activities related to environmental innovation, (b) integrating ecologically sustainable development targets by adopting renewable energy sources, and (c) devising strategies and initiatives to attract foreign direct investment, facilitate knowledge exchange, and promote energy-efficient manufacturing to stimulate economic growth. [ABSTRACT FROM AUTHOR]

Economic agglomeration has played a key function in China's economic transformation. Meanwhile, structural adjustment and external pressure to reduce carbon emission necessitate a deeper investigation into its relationship with carbon productivity. This paper measures economic agglomeration and carbon productivity of 281 cities in China in 2003–2017. With the purpose of exploring the spatial effect of economic agglomeration on carbon productivity, a spatial Durbin model is constructed. In addition, the mediation effect model is also adopted for examining the transmission mechanism of economic scale and technological progress on economic agglomeration as well as carbon productivity. A heterogeneity test is also carried out to uncover the varying effects of economic agglomeration on carbon productivity. The empirical results suggest that economic agglomeration raises carbon productivity not only in the local cities but also in the neighbouring ones. The impact of economic agglomeration on carbon productivity becomes more potent as the level of economic agglomeration increases. For cities with low level of economic agglomeration, the effect is mainly achieved through the expansion of economic scale, but for cities with high level of economic agglomeration, the effect is mainly achieved through technological progress. Therefore, we suggest encouraging carbon productivity improvement through technology effect in cities with high economic agglomeration level, while enhancing carbon productivity through scale effect in cities with low economic agglomeration level. [ABSTRACT FROM AUTHOR]

The carbon emissions trading system (CETS) is a helpful policy instrument for separating carbon emissions from economic expansion, and it significantly impacts energy efficiency (EE). This study uses 30 Chinese provinces from 2007 to 2020 as its research samples, and classifies energy efficiency into single-factor energy efficiency (SFE) and total-factor energy efficiency (TFE), using the difference-in-differences model to examine the effect and mechanism of the CETS on EE. As an additional tool to assess the efficacy of the CETS, the corresponding evolution of the rebound effect of energy-related carbon emissions (RECE) is also calculated. This study shows that the CETS can significantly improve EE in China's pilot provinces. The influence mechanism indicates that the effect of the CETS on EE is influenced by the level of government governance, green innovation, and industrial structure optimization. Further study finds that after the CETS was carried out, the RECE in pilot provinces was higher than that in non-pilot provinces, and 31.4% of carbon emissions reduced by EE improvement rebounded. Therefore, the CETS has yet to realize its full carbon reduction potential. The study offers specific policy proposals for the enhancement of China's CETS in light of the aforementioned findings. [ABSTRACT FROM AUTHOR]

The rising GHG emissions and climate change have resulted in number of catastrophes such as floods, droughts and heat waves. Accordingly, researchers are interested in exploring the nexus between GHG emissions and economic growth. This research study is motivated to explore the moderation of transportation competitiveness for economic growth and carbon emissions of transport sector in global perspective. The annual time series data for study variables are used for time period from 2008 to 2018 for 121 countries. The panel quantile regression (PQR) estimation technique is used for analysis of results. The study results validated inverted U-shaped environmental Kuznets curve (EKC) for quantile group-1 and 2, while U-shaped EKC was validated for quantile group-3 and 4. The moderation of transport competitiveness significantly tends to achieve environmental sustainability for economic growth and carbon emissions of transport sector for quantile group-1 and 2. However, the moderation of transport competitiveness increases carbon emissions of transport sector in quantile group-4. The study results implicated that process of economic growth resulted in expansion of transport sector in quantile group-3 and 4 beyond sustainable level. The various policy recommendations are advocated to improve the quality of transport sector to mitigate carbon emissions. [ABSTRACT FROM AUTHOR]

Exploring the relationship between economic development and carbon emissions is a hot issue of concern to academia. Taking Chinese cities as the research object, this study constructed an allometric growth model of economic scale and carbon emissions to analyze the spatial–temporal evolution of their allometric growth from 2000 to 2017. Additionally, the geographical detector model was used to reveal the driving mechanism of allometric growth. The findings were as follows. (1) The spatial–temporal patterns of economic scale and carbon emissions were dominated by hot spots. Additionally, their size distribution was in an equilibrium stage. (2) The gap between the economic growth rate of Chinese cities and the growth rate of carbon emissions grew, reflecting the remarkable achievements in carbon emission reduction in Chinese cities as a whole. The scaling exponent declined from east to the west during 2000–2008, but showed the opposite trend during 2009–2017. The proportion of cities with negative allometric growth in the sample cities increased from 76.49 to 97.86%. (3) The influence of city investment intensity, energy utilization efficiency, technological development level, social consumption level, fiscal investment level and economic development level on allometric growth gradually decreases. These factors were also the main factors affecting the spatial–temporal heterogeneity of allometric growth. (4) The impact of various factors had a synergetic enhancement effect. These factors can be classified as economic factors, environmental factors and a combination of them. Under the nonlinear coupling of multiple factors, a spatially differentiated pattern of allometric growth was formed. [ABSTRACT FROM AUTHOR]

Financial development is a multidimensional process that contributes to economic growth but sometimes it has a devastating effect on climate change. No country can achieve sustainable development goals without caring the environmental quality. The present study investigates the moderating role of globalization (KOF) in determining the financial development (FD) on environmental degradation in the SAARC countries from 1990 to 2020. The long-run coefficients are estimated using the panel quantile regression (PQR) approach at lower, middle and upper quantile groups. The study shows the U-shaped relationship across three quantile groups based on financial development and carbon emissions. The moderator globalization (KOF) brings up the change in the turning point and flattens before the maturity of the U-shaped curve at the middle quantile while flattens after the maturity of the U-shaped curve at the upper quantile. The study recommends that by using energy-efficient technologies, better financial sector interaction with globalization enhances the environmental quality in SAARC countries. [ABSTRACT FROM AUTHOR]

China is the world's largest energy consumer and CO2 emitter, facing a great challenge of CO2 emission mitigation. In order to identify driving factors for prefecture-level carbon emissions in western China, a case study of Haixi was performed. Time series analysis was undertaken in this study to provide a holistic picture of the historical trend of energy-related CO2 emissions. The relationship between CO2 emissions and economic growth was also explored based on decoupling analysis. Subsequently, logarithmic mean Divisia index was adopted to identify key factors driving CO2 emissions. Results showed that the energy-related CO2 emissions generated by Haixi increased to 18.18 million tons in 2016 from 7.26 million tons in 2007. Results also indicated that Haixi had not achieved decoupling of economic growth from CO2 emissions. Economic activity was the dominant positive driver in changes of CO2 emissions, while industrial structure was the dominant negative driver over the entire period. Suggestions based on empirical findings and local realities were proposed, which may provide reference for stakeholders regarding the reduction of CO2 emissions. [ABSTRACT FROM AUTHOR]

This study seeks to address pertinent economic and environmental issues associated with natural gas flaring, especially for the world's leading natural gas flaring economies (i.e. Russia, Iraq, Iran, the United States, Algeria, Venezuela, and Nigeria). By applying relevant empirical panel and country-specific approaches, the study found that fuel energy export positively impacts economic growth with elasticity of ~ 0.22 to ~ 0.24 for the panel examination. It is further revealed that environmental quality in the panel is hampered by increase in economic growth, gas flaring, fuel energy export, and urbanization. Moreover, for the country-wise inference, government quality desirably moderates economic and environmental aspects of gas flaring in Venezuela and Nigeria, and in Russia and Iran respectively. However, government quality moderates gas flaring to cause economic downturn in the USA. Additionally, economic growth increased with increase in urbanisation (in Iraq and the USA), gas flaring (in Iran and the USA), government quality (only in the USA), and fuel energy export (only in Algeria) while economic growth downturn is due to increase urbanisation in Russia and the USA, increase in fuel energy export in the USA, and increase in government quality in Russia. Meanwhile, environmental quality is worsened through intense carbon dioxide emission from increased urbanisation activity (in Iraq, Iran, Algeria, and Nigeria), increased fuel energy export (in Nigeria), increased natural gas flaring (in Algeria and Nigeria), increased GDP (in Russia, Iran, USA, Algeria, and Venezuela), and high government quality (in Iran). Interestingly, the result revealed that increase in GDP (in Nigeria), increase in urbanisation (in the USA), and increase in gas flaring (in Algeria and Nigeria) dampens environmental quality. Importantly, this study offers policy insight into sustainable approaches in natural gas production, government effectiveness, and regulatory quality. [ABSTRACT FROM AUTHOR]

Financial inclusion is critical element of economic growth as it makes financial services available to all facets of society and hence has an influence on environmental quality. Using data from 2004 to 2019, this research evaluates the asymmetric nexus between financial inclusion and environmental quality in the top-10 polluted nations (China, India, Russia, USA, Japan, Iran, Germany, Saudi Arabia, South Korea, and Indonesia). Previous research used panel data approaches, which resulted in usual findings of the connection between financial inclusion and environmental quality, even with the reality that numerous nations did not show such a linkage individually. This research, conversely, utilizes an exclusive method 'Quantile-on-Quantile (QQ)', which permits us to probe each nation distinctly to provide multilateral yet country-specific information about the relation between the variables. The estimations demonstrate that financial inclusion degrades environmental quality in 7 out of the 10 economies at many quantiles of data distribution. Additionally, the outcomes reveal that the degree of asymmetry between financial inclusion and carbon emissions differs by nation, stressing the need of governments giving particular attention while implementing policies related to financial inclusion and a sustainable environment. [ABSTRACT FROM AUTHOR]

As the world's largest carbon dioxide emitter, China is curbing coal consumption and increasing natural gas and renewable energy consumption to curb the increase in carbon emissions. At the same time, China is still the largest developing country in the world. Therefore, it is very important to investigate the links between different types of energy consumption, economic growth, and carbon emissions. In this paper, impulse response functions and Granger causality test based on time-varying parameters vector autoregressive model are used to explore the time-varying relationship among CO2 emissions, economic growth, and heterogeneous energy consumption (coal, gas, oil, and renewable energy) in China over the period 1980–2019. The results show that reducing coal and oil consumption and increasing natural gas and renewable energy consumption will not significantly hinder economic growth. In addition, in the long run, reducing coal and oil consumption and increasing renewable energy consumption can significantly reduce carbon emissions. However, after 1998, increasing natural gas consumption will significantly increase carbon emissions. This study reveals the time-varying relationship between heterogeneous energy consumption, economic growth, and carbon emissions, and provides suggestions for China to achieve low-carbon economic growth. [ABSTRACT FROM AUTHOR]

A growing body of literature has highlighted the importance of green innovation and institutional quality in sustainability transitions. However, there is little empirical research knowledge about green innovation and institutional quality as significant factors for sustainable development, particularly in Africa. In this context, the study examines the relationship between green innovation, institutional quality, economic growth, export, energy consumption, urbanization, and CO2 emissions in three (3) African countries over the period 1990 to 2016 at a panel and individual country level. Westerlund–Edgerton panel cointegration test together with the Cross-sectional Augmented Dickey-Fulller (CADF) test and Cross-sectional Im, Pesaran and Shin (CIPS) test correspondingly confirmed the variables employed are co-integrated and as well stationary. Major findings from the augmented mean group (AMG) estimator unveiled that: (i) green innovation mitigates CO2 emissions, whereas institutional quality increases CO2 emissions at the panel level and in South Africa; (ii) energy consumption increases CO2 emissions at the panel level and in all the individual countries; (iii) urbanization increases CO2 emissions at the panel and in Egypt and South Africa; (iv) an inverted U-shaped is evidenced to exist among economic growth and CO2 emissions in Egypt and South Africa. Finally, Dumitrescu-Hurlin panel causality test revealed a unidirectional causal link from CO2 emissions to green innovation and institutional quality correspondingly. Policy implications of these findings are discussed. [ABSTRACT FROM AUTHOR]

This paper investigates the association between CO2 emissions and a range of factors, including electricity consumption, economic growth, urbanization, and trade openness for six Gulf Cooperation Council (GCC) countries using data covering the 1965–2019 period. Namely, Oman, Saudi Arabia, the UAE, Kuwait, Bahrain, and Qatar. Contrasting with the standard literature, our empirical strategy uses the wavelet coherence approach on the frequency domain, thought to complement the time series econometric procedures reported earlier on this topic. Supplied at the country level, associated evidence presents far-reaching policy recommendations whose applications may directly benefit environmental planning and bring high information value for the sake of sustainable energies in the Gulf region. [ABSTRACT FROM AUTHOR]

A major concern for the modern world is to deal with environmental issues without compromising on economic growth targets. Energy use from renewable and nuclear sources offers a solution to this issue. Therefore, the present study is an attempt to examine the nexus between disaggregated energy consumption, economic growth and carbon dioxide emissions. To this end, a sophisticated econometric technique proposed by Machado and Silva (J Econom 213:145–173, 2019. https://doi.org/10.1016/j.jeconom.2019.04.009) is used for a sample of 107 countries during 1996–2014. For robustness analysis, fixed and random effect with Driscoll Kraay standard errors model is used. The findings revealed an inverted N-shape EKC showing that nuclear and renewable energy alleviate pollution while non-renewable energy enhances it. Interestingly, the impact of nuclear and renewable energy is stronger at lower quantiles than at higher ones. Findings highlight the need for promoting nuclear and renewable energy to combat environmental challenges. Therefore, an adequate plan promoting the use of renewable energy should be established to ensure successful energy transition and reap its benefits in terms of economic development and environmental protection. In addition, important policy implications are suggested based on the findings of the study. [ABSTRACT FROM AUTHOR]

This research examines the potential impact of economic growth, carbon emissions, trade, and energy use on tourism development in Pakistan from 1980 to 2018. This study employed the Autoregressive Distributed Lagged technique for the simultaneous estimations of short and long-run associations. The study found a positive impact of energy use, economic growth, and trade openness on tourism development in the short and long run. On the other hand, the study reveals a negative impact of CO2 emissions on tourism development in Pakistan. The study further applied an innovative accounting approach for robust results of the study. The study based on Toda Yamamoto causality approach revealed unidirectional causal association among the study variables. The results, thus, suggest the change in investment decisions as the government and policy makers should encourage investments in services sector rather than polluting industrial sector as the services sector is less polluting and leading sector of the economy. This, in turn, could help attract tourists due to environmentally and economically sustainable growth. [ABSTRACT FROM AUTHOR]

This study examines the association between renewable energy strategies and carbon emissions on sustainable economic growth under affordable and clean energy sources to achieve sustainable development goal seven. This research provides new insight by exploring the nexus between environmental pollution and the creation of numerous bases of renewable energies, such as hydropower, wind power, biomass, geothermal, and solar photovoltaic, and economic growth epitomizing capital, trade openness, and government spending. Moreover, this investigation uses second-generation devices for econometric investigation and a heterogeneous methodology for panel data for selected Asian countries. The empirical exploration of long-term influences drove by the Common Correlated Effects Mean Group, close by Augmented Mean Group and Mean Group assessors confirm the positive and significant influence of renewable energy like hydropower, solar photovoltaic, wind, biomass, and geothermal on the economic growth of Asian economies. Study findings provide valuable insights for all stakeholders in an integrated and coherent manner. [ABSTRACT FROM AUTHOR]

The primary aim of this study is that whether Granger causality (GC) among CO2 emissions, energy consumption (EC) and economic growth (EG) in different regimes in Iran is similar and sustainable. We answer this question using Markov Switching Vector Autoregressive (MS-VAR) approach and the quarterly data from 1970Q1 to 2015Q4. The findings show that the causal relationship switches among these variables in different regimes. In the first regime, the results show a positive unilateral GC from EG to EC. In the second regime, the study shows a negative GC from EC to EG, and a positive causality from EG to EC, and a negative unilateral causality from CO2 emissions to EG. The results indicate no causality from EG and EC to CO2 emissions in the first and second regimes. The results further show that the probability of sustainability in this first regime, where the rate of EG is at a low level but the amounts of EC and CO2 emissions are at a high level, will be high compared to the second regime. These findings call for more attention to the various effects of these variables on each regime before the policy implementation. [ABSTRACT FROM AUTHOR]

Economic structural changes are a major factor that has a big impact on most of a country or region's economic systems and operations, as well as the environment. This study looks at how conventional energy-based power use affects carbon emissions in Pakistan through a structural change analysis of the country from 1971 to 2018. It uses the autoregressive distributed lags (ARDL) method and covers the period from 1971 to 2018. The long-term findings from the ARDL suggest that economic expansion, growth and development, and agro production lead to declining carbon emissions and in turn, will improve the state of the environment. Precisely, an increase in 1% of economic expansion and agricultural production will reduce carbon emissions by 1.26% and 0.53%, respectively. However, the current use of conventional energy to make electricity is causing carbon dioxide to be released into the air. People who live in cities use more conventional energy, which means that the amount of carbon dioxide they produce will go up by 1.53% for every 1% change in conventional energy use. This means that there are strong links between urbanzation and carbon emissions. Government and industry policymakers should encourage people to use renewable and conventional energy sources, encourage them to invest more in green-related businesses, and provide more social amenities and better infrastructure in Pakistan's rural areas, to name a few things. Doing so will help to reduce the continuing and uncontrolled influx of people to the country's cities, which simply further endangers the natural environment. [ABSTRACT FROM AUTHOR]

Primarily, the current study seeks to explore the influence of financial development, economic growth, trade openness, non-renewable and renewable energy utilization on carbon dioxide (CO2) emission in Pakistan from 1990 to 2017. The findings of structural break unit root tests indicated that a few variables are stationary at the level and others integrated at the first difference. The bound F-test and Johansen cointegration tests confirmed the evidence that a long-run relationship exists among concerned variables. The long-run results explore that financial development and renewable energy penetration significantly accelerate the environmental quality, while economic growth, non-renewable energy utilization, and trade openness are responsible for deteriorating the environmental quality. The results from the short-run estimate explore that non-renewable energy utilization and trade openness significantly reduce the environmental quality while renewable energy sources are beneficial for environmental quality. Moreover, the current study discovered the unidirectional Granger causality relationship from economic growth, trade openness, non-renewable and renewable energy penetration to carbon emission in Pakistan. The outcomes of this study provide some insightful policy suggestions to overcome the detrimental effect of environmental degradation. [ABSTRACT FROM AUTHOR]

This study attempts to explore the environmental impacts of globalization under the umbrella of the EKC (environment Kuznets curve) approach in South Asia. For this reason, this study investigates the causality between energy usage and growth-driven CO2 emanations. The study adopts the FMOLS (fully modified OLS) technique for the econometric assessment, which portrays a significant demolish of environmental well-being in the region, whereas individual country, such as Nepal, also demonstrates a positive and significant effect of non-environmentally friendly power and globalization index on CO2 emanations. Nonetheless, negative as well as positive signs of GDP and its square (GDP)2, respectively, validate the EKC theory in the sample region. Furthermore, the empirical finding reveals the feedback effect between economic growth (GDP) and energy usage. Despite this, GDP Granger causes CO2 emanations. [ABSTRACT FROM AUTHOR]

Background: This study revisits the energy-growth-environment nexus in the member countries of the Organization for Economic Cooperation and Development (OECD) by examining the role of trade openness, financial development, and urbanization. The cross-sectional augmented distributed lag (CS-ARDL) approach is employed to address the presence of slope homoskedasticity and cross-sectional dependence in the data set. Results: Our empirical findings fail to confirm the validity of the environmental Kuznets curve (EKC) hypothesis for emissions of carbon dioxide (CO2) during the period researched. CO2 emissions have bidirectional causality with income, the share of renewable energy, and the share of nonrenewable energy. Trade openness, financial development, and urbanization play different roles in the energy-growth-environment nexus. Whereas trade openness increases CO2 emissions, financial development reduces consumption of renewable energy. Urbanization plays a limited role in this nexus. Conclusions: These findings lead to some policy implications. The close relationship between economic growth, CO2 emissions, and energy consumption is highlighted, which suggests that a policy targeting one component needs to consider the impacts on the other components. [ABSTRACT FROM AUTHOR]

Global climate change caused by greenhouse gases (GHGs), particularly carbon dioxide (CO2) emissions, poses incomparable threats to the environment, development, and sustainability. This research investigates the potential of economic growth, renewable energy use, and technological innovation to achieve Malaysia's Paris Agreement by reducing CO2 emissions. Time-series data from 1990 to 2019 were utilized applying the Dynamic Ordinary Least Squares (DOLS) method. The empirical findings show that the coefficient of economic growth is positive and significant with CO2 emissions, indicating a 1% increase in economic growth is related to a 0.9% rise in CO2 emissions. Furthermore, the coefficient of renewable energy use is negative and significant, which indicates that increasing renewable energy use by 1% is associated with CO2 emissions reduction by 0.3% in the long run. In addition, increasing technological innovation lowers CO2 emissions, implying that a 1% increase in the number of patent applications is linked to a 0.05% reduction of CO2 emissions. The empirical findings reveal that increased renewable energy use and technological innovation can reduce Malaysia's carbon emission while economic growth deteriorates the environmental quality. Thus, effective implementation of policy measures to a low-carbon economy, promoting renewable energy use, and financing technological innovation could help to achieve Malaysia's Paris Agreement by reducing CO2 emissions. [ABSTRACT FROM AUTHOR]

It is a global challenge to achieve sustainable economic growth by improving the environment. The present study discussed the role of the financial development sector in achieving sustainable economic growth and environmental quality in South Asian countries from 1990 to 2020 by controlling labour force participation, globalization, industrialization, and the education sector. A feasible generalized least squares (FGLS) panel data econometric technique has been used to check the relationship among the variables. The results show that financial development has a U-shaped relationship with carbon emissions and economic growth. Furthermore, labour force participation, industrialization, globalization, and educational school enrolment significantly increase CO2 and economic growth. This study suggests that the governments of South Asian countries should take steps to increase economic growth. For this purpose, effective supervisory mechanisms of financial development through financial innovation, improving financial efficiency, maintaining financial stability, and reducing the environmental pollution. [ABSTRACT FROM AUTHOR]

Although energy supply is not the only factor of the production function, it remains an important driver for any economy despite its negative environmental impacts. This paper examines the determinants of carbon dioxide emissions in a sample of 35 African countries from 1980 to 2016. It uses several econometric methods to ensure robust and reliable findings. Results from Mean group (MG) and Dynamic common correlated effects mean group (DCCEMG) models prove that the environmental degradation in the selected sample is caused mostly by economic growth and non-renewable energy consumption. Moreover, the results confirm that the Environmental Kuznets Curve hypothesis is not significant when consider cross sectional dependence. These finding are contradictive to those obtained from similar studies that used traditional panel estimators. This means that energy consumption and economic growth will continue to increase emissions in the future. Furthermore, the study provides evidence of bidirectional causal relationships between carbon dioxide emissions and economic growth, non-renewable energy consumption and economic growth and between non-renewable energy consumption and carbon dioxide emissions. These findings imply that a hard work must to be done by the African policymakers and a long corrective measure series have to be adopted to ensure more efficient and clean energy. [ABSTRACT FROM AUTHOR]

This paper is aimed at examining the short- and long-run relationships among consumption of renewable and non-renewable energies, economic growth, and CO2 emissions in Mexico during the period 1973–2018. Data were obtained from the World Bank and the British Oil Company BP. A cointegration model together with a fully modified ordinary least squares (FMOLS) is used to estimate possible associations among all variables. Subsequently, the Granger causality test is applied to empirically verify the environmental Kuznets curve (EKC) hypothesis. The main empirical results are that the variables under study explain CO2 emissions in the short and long run, with economic growth having the greatest influence on CO2 emissions, which provides empirical evidence of an EKC for Mexico. Moreover, consumption of renewable and non-renewable energies and economic growth causes in the Granger sense the current levels of CO2 emissions. Moreover, lagged GDP and lagged non-renewable energy consumption do influence (Granger cause) current CO2 emissions. Long-term policies should encourage the use of renewable energies in the electricity, transport, manufacture, and construction sectors. [ABSTRACT FROM AUTHOR]

Carbon emissions and economic growth are two contradictions in urban development, and their decoupling is related to the sustainable development of cities. This paper took urban agglomeration in the middle reaches of the Yangtze River (UAMRYR), China, as the study area. The Kaya model, the Tapio decoupling model, and the Logarithmic Mean Divisia Index (LMDI) model were adopted to analyze the spatiotemporal differentiation of carbon emissions, the decoupling of economic activities, and driving factors. The results indicate that (1) carbon emissions increased by 66% in the study period, but the growth momentum was curbed after 2015. Low level and medium level areas continue to decrease, and relatively high level area gradually become dominant. (2) Spatially, carbon emissions are in a pattern of middle-hot and east-cold. Jiangxi is in the sub-cold and coldspot area, while the hotspot area is driven by the transformation from Wuhan's single-core to Wuhan and Changsha's dual-core. (3) Since 2010, most cities have been in a good decoupling state, and weak decoupling cities have risen from 35.5% in the initial period to 87.1% in 2010–2011, but the decoupling situation of industrial cities with more high-energy-consuming industries still rebounded slightly. (4) The economic level and energy intensity effect had the most significant impact on the economic decoupling of carbon emissions, whose absolute contribution rates were greater than 35%. Urbanization and economic level both play a positive role in promoting carbon emissions, and the energy intensity plays a negative role in retarding carbon emissions. The population effect was mainly manifested in carbon increase from 2006 to 2011, and 45.2% of the cities from 2011 to 2017 turned into carbon suppression. Finally, we suggest that decoupling carbon emissions from economic growth requires developing green urbanization and a decarbonized economy, optimizing the structure of energy consumption and guiding rational population flow. [ABSTRACT FROM AUTHOR]

Since global warming worsens with economic development and emitted CO2 is one of the main greenhouse gases, it is important to understand the relationship between CO2 emissions and economic growth. The paper applies a new panel cointegration test with cross-sectional dependence and structural breaks to examine this relationship in developed and developing countries, respectively. The results indicate that the "Environmental Kuznets Curve" does not hold in either group. For developing countries, there is neither linear nor quadratic long-term equilibrium relationship between CO2 emissions and economic growth. For developed countries, the quadratic relationship does exist between CO2 emissions and economic growth, whereas the linear one does not. A half of these countries have inverted U-shaped curves, while the other half have U-shaped curves. Besides, most of these countries are still on the rising stage of the curve. This paper gives new insights for policymakers to keep a balance between sustainable economic growth and suitable environmental quality. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to analyze the relationship between urban public infrastructure, CO2 emissions and economic growth in China for the period 1990–2019 using the Dynamic Conditional Correlation Multivariate GARCH model (DCC-MGARCH) and Autoregressive Distributed Lagged Model (ARDL). According to the estimated results of the DCC-MGARCH, there is a positive influential effect among the economic growth, urban public infrastructure and CO2 emissions, while there is a negative influential effect between the urban public infrastructure and CO2 emissions, but the duration of volatility between the urban public infrastructure and CO2 emissions is relatively weak. Among such relationships, the conditional correlation also shows there is an effect in S-shape between the urban public infrastructure and economic growth, but the trend variation between the urban public infrastructure and CO2 emissions shows an inverted "U-shape" of Environmental Kuznets Curve Theory. The results of the ARDL-Bounds test show that there are long-term co-integration relationships and short-term dynamic correlation among all models. Also, the results of error correction terms show that the speed deviating economic growth and CO2 emissions from the long-term equilibrium and CO2 emissions deviating from the long-term equilibrium is larger than that of the urban public infrastructure, which indicates that the relationship between the economic growth and CO2 emissions is relatively strong. [ABSTRACT FROM AUTHOR]

The current study investigates the causal relations between CO2 emissions and the growth of Nigeria's economy, a topic of significant interest for the relevant authorities that has yet to be comprehensively examined. We test both the nonlinear and time-varying nature of the variables' relationships to provide effective and applicable policies. Unlike the linear method's lack of causal evidence, both nonlinear and time-varying Granger causality tests indicate the presence of dual causation between the variables. This suggests that appropriate and cost-effective environmental policies need to be adopted in Nigeria to prevent sustainable economic growth from being jeopardized while addressing environmental concerns. In this regard, it is recommended that clean energy resources make a greater contribution to the country's energy paradigm as a viable solution. This will lead to higher energy efficiency, which will help the country to maintain the economy's growth level in the ideal zone and mitigate environmental challenges. [ABSTRACT FROM AUTHOR]

This paper proposes the projected gradient algorithm to find a solution that allows economic restructuring to minimize carbon emission intensity and not hinder targeted economic growth. It develops a general formula to calculate how much each sector should change its share in gross domestic products and its emission intensity such that the economy can have a lower aggregate emission intensity without hindering economic growth. Used data for 30 nations during 1997–2009, the study indicates that if a country follows this proposed optimal restructuring solution, it experiences a lower carbon emission intensity than its initial scenario. This solution is helpful to (1) find the optimal direction and quantitative solutions of a low emission economic structure; (2) continuously check and quantify the differences between the optimal and actual directions of economic structuring for adjusting economic and environmental policies. [ABSTRACT FROM AUTHOR]

Carbon dioxide emissions have been the primary source of extreme environmental pollution and have detrimental consequences on human life, irrespective of an economy being developed or underdeveloped. For the developing economies, in particular, it is imperative to reduce such emissions in order to sustain the growth of the respective economies. However, for designing appropriate emission reduction policies, it is appropriate to identify the sectors which contribute the most to carbon dioxide emissions and dampen the growth of overall economy. Against this background, the key intention of this study was to examine the influence of carbon dioxide emissions generated from various sources on the economic progress in Pakistan between 1971 and 2017. This study is important for Pakistan to sustain its economic progress and enable the nation to comply with commitments of the Paris Agreement and Sustainable Development Goals. The econometric analysis conducted in this study considers a nonlinear autoregressive distributed lag model which is applied to ascertain the short- and long-run economic growth impacts associated with positive and negative shocks to CO2 emissions generated from various sources. The choice of this model is driven by its capacity to perform an asymmetric analysis which is relevant for suitable policy-making purposes. The overall results, in a nutshell, reveal that carbon dioxide emissions from Pakistan's transportation sector influence the country's economic progress. Positive shocks to such carbon dioxide emissions are originate to reduce economic progress in the long run while negative shocks are evidenced to boost economic growth both in the short and long run. In contrast, carbon dioxide emissions from other major sectors are found to be ineffective in influencing Pakistan's economic growth both in the short and long run. Hence, keeping into consideration the prospects of attaining sustainable economic growth, the Pakistan government must prioritize the implementation of CO2 emissions-inhibiting policies within the transportation sector. Simultaneously, the traditional fossil fuel dependency within this sector should also be phased out. [ABSTRACT FROM AUTHOR]

The current paper empirically investigates the effect of environmental stress on economic growth in the Gulf Cooperation Council countries during 1995–2016. A panel cointegration analysis, specifically an autoregressive distributed lag model, is used to achieve the paper's goal. The present work is motivated by the high carbon dioxide emissions per capita and environmental stress in these countries relative to other countries, and it assumes that the income per capita is a function of the natural resource's rents and environmental stress. The findings show that environmental stress enhances economic growth, mainly in the long run. At the same time, the natural resources' rents improve it in the short run and impede it in the long run. These results are significant because they tell that the Gulf Cooperation Council countries' environmental stress did not reach critical levels that produce vast negative influences on the economy, and the resource curse hypothesis is valid in the long run. The current study's policy implication states that economic policymakers should monitor and evaluate future environmental stress outcomes in these countries. There is no guarantee that the positive influence prevails. Therefore, the Gulf Cooperation Council countries should adopt genuine procedures to diversify their economies. Besides, it should continue its initial steps to expand renewable energy resources, i.e., nuclear, wind, and solar. [ABSTRACT FROM AUTHOR]

The energy–environment–growth nexus has been examined for the Association of Southeast Asian Nations (ASEAN) region, mainly using time series data. However, the important role of renewable energy and population has largely been ignored in previous studies. As such, this study is conducted to investigate a causal link between renewable energy usage, population, carbon dioxide emissions, and economic growth. In addition, a relatively new and advanced panel vector autoregressive model and the Granger non-causality test for heterogeneous panels are utilized with a sample of seven ASEAN countries for almost three decades since 1990. Key findings from this paper are as follows. First, renewable energy usage responds to population growth and leads to carbon dioxide (CO2) emissions. Second, economic growth and renewable energy usage explain a substantial proportion of the change in energy consumption. Third, a bidirectional Granger causality does exist in each pair among energy consumption, economic growth and CO2 emissions. We argue that moderating population growth and extending renewable energy usage are vital to achieving sustainable economic growth in the ASEAN region. [ABSTRACT FROM AUTHOR]

We parallelize the extended path method for solving rational expectations models, and apply it to compute perfect foresight competitive equilibrium for the global economy with multiple goods, regions, industries, and households. At each iteration, first intertemporal variables are updated, then equations for intra-temporal variables are solved in parallel. We compare serial, and parallel, versions of the extended path method in high-performance computing environments based on scenarios with long time horizons that include future populations, economic growth, energy use, and carbon dioxide emissions. Relative to the serial version, the speedup factor for the parallel extended path method grows almost linearly up to about 30 times with 18 cores, and computing times reduced from over 10 h for the serial version down to about 20 min for the parallel version. [ABSTRACT FROM AUTHOR]

This paper examines the impact of energy efficiency (EE) and renewable energy (RE) on carbon emissions, using a panel data of South Asian countries over the period 1990–2014. The empirical investigation involves the estimation of a panel autoregressive distributed lag model in a multivariate framework by employing the pooled mean group estimator. The estimates are presented for homogenous long-run effects and heterogeneous (country-specific) short-run effects of EE and RE on carbon emissions. The estimated results suggest that a cointegrating link is evident between carbon emissions, EE and RE in South Asian countries, especially after controlling the effects of economic growth and trade openness. The homogenous coefficient estimates reveal that in the long run, carbon emissions decline with a rise in RE, but emissions increase with an improvement in EE. Moreover, heterogeneous coefficient estimates indicate that in the short run, both low-carbon strategies (EE and RE) are effective for India and Nepal. However, only one strategy is effective for Pakistan, Bangladesh and Sri Lanka, that is, RE, RE and EE, respectively. The findings of this study provide new and valuable insights about the impact of EE and RE on carbon emissions in South Asian countries. Based on the results of this study, several crucial suggestions and implications are deliberated to promote long-term environmental sustainability in the region. [ABSTRACT FROM AUTHOR]

This study examined the nexus between urbanization and carbon emissions in West Africa. Second-generation econometric techniques that are robust to cross-sectional dependence and slope heterogeneity were used for the study. From the Pesaran–Yamagata homogeneity test, the slope coefficients were heterogeneous in nature. Also, the Breusch–Pagan LM test, the Pesaran scaled LM test, bias-corrected LM test, Pesaran CD test and the Friedman's test confirmed the studied panels to be cross-sectionally dependent. Further, the CADF and the CIPS unit root tests established the variables to be first-differenced stationary. Additionally, the Westerlund and Edgerton bootstrap cointegration test and the Pedroni residual cointegration test affirmed the series to be cointegrated in the long run. The Driscoll–Kraay standard errors regression estimator was employed to examine the long-run equilibrium relationship amid the series, and from the results, urbanization had a significantly positive influence on CO2 emissions in all the three panels. Also, economic growth had a materially positive effect on CO2 emissions, while renewable energy consumption had a substantially negative impact on CO2 emissions in all the panels. The causal connections amid the series were finally explored through the Dumitrescu–Hurlin panel causality test, and the discoveries were a bit varied across the various panels. Policy recommendations are further discussed. [ABSTRACT FROM AUTHOR]

The survey explores the relationship between growth determinants on carbon emissions of 44 countries in Sub-Saharan Africa for the duration 1990–2014. The research applies Dumitrescu and Hurlin's Granger causality and pooled mean group models to analyse data. A two-way (bidirectional) involving environmental quality (emissions) and the following variables—economic growth, renewable energy consumption, industrial practice and financial development, is established. A one-way (unidirectional) causality out of actual development of agriculture to carbon emissions as well as human capital to emissions is apparent. Moreover, economic growth illustrates a positive and significant link with emissions, and the opposite is true for renewable energy consumption in both periods (short-run together with long-run). Financial development shows a negative and insignificant link with environmental quality in the short-term although in the long-term that connection is significantly positive. Industrial practice is significantly positively associated with emissions in the short-term and significantly negatively connected with emissions in the long-term. The actual development of agriculture illustrates an insignificantly positive connection with emissions in the short-term but such a link is positively significant in the long-term. Human capital indicates an insignificantly positive association with environmental quality in the short-run although the result changes to being significantly negative in the long-term. The study generally demonstrates that these country growth determinants in SSA still add increasing levels of carbon emissions in practice. [ABSTRACT FROM AUTHOR]

Central Asia is a major emerging energy player but is also affected by global climate change. To both maintain its economic growth and cope with climate change, Central Asia is in urgent need of environmental and sustainable energy strategies, as well as effective carbon emissions mitigation. To this end, we investigated the characteristics of country-level total carbon emissions in Central Asia (i.e., Kazakhstan, Uzbekistan, Turkmenistan, Kyrgyzstan, and Tajikistan). Then, the logarithmic mean Divisia index method was applied to identify and quantify the driving forces behind the changes in carbon emissions. In addition, country-level long-run relationships between economic growth and carbon emissions were tested by means of the environmental Kuznets curve hypothesis. The results are as follows. (1) There were pronounced differences in per capita gross domestic product, energy intensity, and carbon emissions structures across this region, mainly owing to the oil and gas endowment and economic development stage. (2) Impacts and influences of various drivers of carbon emissions varied across countries over the different stages. (3) During the economic recession period, carbon emissions decreases were largely driven by the decreasing economic growth effect associated with political instability. (4) During the economic transition periods, economic growth effect played a dominant positive role in accelerating carbon emissions in the five countries, followed by the population scale effect. Energy intensity effect was the most important factor in curbing carbon emissions in the five countries. Emissions increases during these periods were partly or largely compensated by the improving energy intensity in the different countries. Carbon intensity effect mostly had a negative but relatively minor effect on carbon emissions. (5) There was only an inverted U-shaped curve existing in the lower-middle-income country (Uzbekistan). Considering these differences and disparities in emissions characteristics and determinants can provide important insights for the energy sustainability and carbon mitigation in Central Asia. [ABSTRACT FROM AUTHOR]

Correction to: Do Energy Resources matter for Growth Level? B Correction to: Clean Technologies and Environmental Policy b https://doi.org/10.1007/s10098-022-02432-9 In the original publication, the affiliation information of all the authors was processed incorrectly. Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. [Extracted from the article]