A comparative analysis of the relationship between innovation and transport sector carbon emissions in developed and developing Mediterranean countries

Integrating climate resilience with sports, exercise, and public health expenditures on sustainable environment: Evidence from coastal regions of China

The adoption of environmentally-friendly habits has become more crucial in the present period as a means to mitigate the rate of environmental degradation and its detrimental consequences. The augmentation of sports, exercise and physical activities has been associated with favourable health outcomes, in addition to the ability to mitigate carbon emissions resulting from vehicular transportation. Consequently, the objective of this study is to examine the influence of sports, exercise, and physical activities, along with public health expenditure, on the environmental performance of China's coastal regions throughout the period spanning from 2010 to 2019. The proposed study employs the Feasible Generalized Least Squares (F.G.L.S) and the Generalized Method of Moments (G.M.M) methodologies. Results show that participation in sports and other forms of physical activity significantly improves environmental performance in China's coastal areas. Likewise, a robust negative correlation exists between air pollution and healthcare expenses, hence favouring enhanced environmental outcomes. Nevertheless, it is important to acknowledge that economic expansion has a direct correlation with increased emissions, hence harming environmental performance. There exists compelling evidence indicating a significant impact on environmental quality resulting from the combined influence of heightened health expenditures and increased engagement in sports. This is demonstrated by the presence of an interaction term between health expenses and sports activities. The findings of this study suggest that there is a requirement to re-evaluate healthcare spending initiatives and sporting activities in order to effectively pursue carbon neutrality goals and improve environmental sustainability.

Spatiotemporal evolution trend and decoupling type identification of transport carbon emissions from economic development in China

Carbon emissions are a major concern in China, and transportation is an important part of it. In this paper, data on China's 30 provinces' transport carbon emissions from 2005 to 2019 were selected to construct a spatial autocorrelation model and identified the decoupling types, which revealed the relationship between transport carbon emissions and economic development. This study suggests a regulation strategy for provincial transport carbon emissions in China based on the contribution rates of transport carbon emission variables. According to the findings, transport carbon emissions of China indicated a slow rise from 2005 to 2019, the annual growth rate has fluctuated downward, and petroleum products have been the most major source. The geographical correlation of transport carbon emissions has gradually improved, and the transport carbon emission intensity has become more significant. Differences in the transport carbon emission intensity slightly increased, which were significantly regionally correlated. There were seven forms of decoupling between yearly provincial transport carbon emissions and economic development, with weak decoupling accounting for the largest proportion, 45.24%. Decoupling was achieved in 83.33% of the provinces in the period of 2005-2019. As a consequence of factor decomposition, the energy intensity, transport intensity, and economic structure played an overall inhibitory role, while the carbon emission intensity, economic scale, and population played promoting roles. The economic scale was the most important influencing factor.

Testing the impact of renewable energy and oil price on carbon emission intensity in China's transportation sector

As the largest carbon emitter in the world, with its transportation sector contributing the largest shares of its emission, the need for a low-carbon transition economy has become a policy agenda for China because in order to reach carbon neutrality by 2050, lowering the intensity of carbon emissions in the transportation sector will be crucial. In this regard, we used the "bootstrap autoregressive distributed lag model" to explore the impact of clean energy and oil prices on the intensity of carbon emissions in China's transportation sector. The study found that an increase in oil prices decreases the intensity of carbon emissions in the short and long run. Similarly, an increase in the level of renewable energy and economic complexity declines the intensity of carbon emissions in the transportation sector. On the contrary, the research demonstrates that non-renewable energy contributes positively to carbon emission intensity. Therefore, the authorities must promote green technology to neutralize the transportation system's detrimental effects on China's environmental quality. The implications for successfully promoting carbon emission intensity mitigation in the transportation sector are examined in the conclusion.

Probing environmental sustainability pathways in G7 economies: the role of energy transition, technological innovation, and demographic mobility

Global warming remains the most devastating environmental issue embattling the global economies, with significant contributions emanating from CO₂ emissions. The continued rise in the level of greenhouse gas (GHG) emissions serves as a compelling force which constitutes the core of discussion at the recent COP26 prompting nations to commit to the net-zero emission target. The current research presents the first empirical investigation on the roles of technological advancement, demographic mobility, and energy transition in G7 pathways to environmental sustainability captured by CO₂ emissions per capita (PCCO2) from 2000 to 2019. The study considers the additional impacts of structural change and resource abundance. The empirical backings are subjected to pre-estimation tests consisting of cross-sectional dependence, second-generation stationarity, and panel cointegration tests. The model estimation is based on cross-sectional augmented autoregressive distributed lag, dynamic common correlated effects mean group, and augmented mean group for the main analysis and robustness checks. The findings reveal the existence of EKC based on the direct and indirect effects of the components of economic growth. The indicators of demographic mobility differ in the direction of influence on PCCO2. For instance, while rural population growth negatively influences PCCO2 in the short-run alone, urban population growth increases PCCO2 in the short-run and long-run periods. Nonrenewable energy, information computer technology (ICT) imports, and mobile cellular subscriptions serve as positive predictors of PCCO2, while ICT exports and renewable energy moderate the surge in PCCO2. Policy implications that enhance environmental sustainability are suggested following the empirical verifications.

Examining the drivers of agricultural carbon emissions in Africa: an application of FMOLS and DOLS approaches

The major aim of this study was to investigate the impact of renewable energy consumption and agricultural economic growth on agricultural carbon emissions in Africa for the period 1990-2019. This paper employed panel fully modified ordinary least square (PFMOLS) and dynamic ordinary least square (PDOLS) estimation techniques. The empirical results showed that agriculture growth promote agricultural carbon emissions. More precisely, the results revealed a strong positive and statistical significant impact on agricultural carbon emissions in Africa. On the other hand, the results on quadratic show a negative causal association between agriculture growth and agricultural carbon emissions in Africa. Interestingly, renewable energy consumption was found to have a negative impact on agricultural carbon emissions. On Granger causality, the result shows that there is a unidirectional causality between agriculture growth and agricultural carbon emissions. Based on these findings, we recommend that countries should promote and encourage the use of renewable energy to curb agricultural carbon emissions. There is a need to adopt agricultural practices that have the potential to limit carbon emissions.

The relationship between renewable energy consumption, technological innovations, and carbon dioxide emission: evidence from two-step system GMM

Large amount of energy use for rising economic growth leads to high carbon dioxide discharge that worsens environmental quality which is a challenge for countries in achieving sustainable development. Improved level of technological innovations and renewable energy consumption might overcome the issue of environmental degradation and achieving sustainable development. This study examines the effect of technological innovations on renewable energy consumption and carbon dioxide emission in the belt and road initiative countries for the period of 1995 to 2019. Two-step difference and two-step system GMM models were employed for analysis where the results indicate that technological innovations increase renewable energy consumption and carbon dioxide emission. The effect of renewable energy consumption and trademark applications on carbon dioxide is negatively significant that raises environmental quality. Furthermore, this study confirms the validity of Environmental Kuznets curve hypothesis in the sample countries. The findings of this study have considerable policy implication for the sample countries on rising technological innovations and renewable energy consumption in achieving environmental sustainability.

Study of the Impact of Industrial Restructuring on the Spatial and Temporal Evolution of Carbon Emission Intensity in Chinese Provinces-Analysis of Mediating Effects Based on Technological Innovation

Global warming caused by greenhouse gas emissions seriously threatens a region's sustainable environmental and socioeconomic development. Promoting industrial restructuring and strengthening technological innovation have become an important path to achieving pollution and carbon reduction as well as the green transformation of economic structure. This paper explored the mechanism of the mediating effect of technological innovation on industrial restructuring and carbon reduction while accounting for the direct effect of industrial restructuring on carbon emissions. Then, based on China's provincial panel data from 2001 to 2019, we estimated the carbon emission intensity using the Intergovernmental Panel on Climate Change (IPCC)'s methods and analyzed its spatiotemporal evolution characteristics. Finally, we constructed a fixed-effect model and a mediating effect model to empirically analyze how industrial restructuring and technological innovation affect carbon emission intensity. The results are as follows: (1) From 2001 to 2019, China's carbon emission intensity showed a continuous downward trend, with a pronounced convergence trend; there were obvious differences in carbon emission intensity between eastern, central, and western regions (western region > central region > eastern region) due to the unbalanced industrial structure. (2) In terms of direct effects, industrial restructuring can significantly reduce carbon emission intensity. The intensity of the effect is inversely proportional to the level of industrial restructuring, and the results of sub-regional tests are similar. Nevertheless, there is an obvious regional difference in the size of the carbon emission reduction effect of industrial restructuring in the east, central, and western regions. (3) In terms of indirect effects, industrial restructuring can reduce carbon emission intensity by enhancing technological innovation, and it acts as a mediating variable in the process of industrial restructuring to reduce carbon emission. Finally, we put forward recommendations for promoting industrial restructuring, strengthening green technological innovation, and properly formulating carbon reduction measures to provide a reference for countries and regions to achieve the goals of carbon neutrality, carbon peaking, and high-quality economic development.

The environmental aspects of renewable energy consumption and structural change in Sweden: A new perspective from wavelet-based granger causality approach

The current paper assessed the time-frequency analysis interrelationship between CO₂ emissions and financial development, economic growth, renewable energy use, structural change, and non-renewable energy use in Sweden. We utilized a quarterly dataset stretching from 1980-2019. In order to unlock these interrelationships, we leverage wavelet tools (wavelet-based Granger causality and wavelet coherence). The wavelet-based Granger causality (WGC) test accounts for the issue of multiple time scales in a time series analysis. Another uniqueness of the WGC lies in its resistance to distribution assumption and misspecification in a time series model. Additionally, the wavelet coherence estimator instantaneously evaluates correlation and causality among the interacting indicators in a model. The outcomes of the wavelet coherence exposed that renewable energy, financial development, economic growth, structural change, and trade openness enhance the environment's quality while non-renewable energy intensifies CO₂. Moreover, the WGC shows that all the variables can predict each other. Based on these findings, policymakers in Sweden should focus more on improving public understanding of renewable energy and environmental preservation. We believe that Sweden's shift to service-sector-led growth will help to safeguard the environment.

Transportation moderation in agricultural sector sustainability - a robust global perspective

The agriculture sector creates nearly a quarter of the total GHG emissions globally as production and transportation activities in the agriculture sector mostly use fossil fuels, creating carbon emissions. In this regard, it is highly important to study the environmental sustainability of agriculture sector growth by using the theory of environmental Kuznets curve (EKC). Furthermore, this research study is aimed to assess the moderation role of transportation competitiveness in determining the carbon emissions of transportation sector by using agriculture sector value addition. The study uses panel quantile regression technique for data analysis of 121 countries by covering time period from 2008 to 2018. The study results validated the agricultural EKC across four different quantile groups based on carbon emissions of transport sector. The moderation of transportation competitiveness is observed in changing the turning point and flattening of agricultural EKC indicating the early achievement of maturity. The quality of institutions and planned increase of population can help reduce carbon emissions of transportation sector. The moderation of transportation competitiveness implicates the importance of planning and efficiently operating the transportation sector to mitigate carbon emissions.

Renewable Energy and Carbon Emissions: New Empirical Evidence from the Union for the Mediterranean

This approach focuses on the renewable energy–carbon emission nexus by delivering new empirical evidence from 37 members of the Union for the Mediterranean. The approach makes use of panel data for the period 2002–2018 and uses panel data econometrical approaches, which are panel random effects regression, feasible generalized least squares regression, and the difference-generalized method of moments estimation, to understand how agricultural activity, economic growth, and renewable energy use impact carbon emissions. The results indicate that economic growth increases carbon emissions, whereas renewable energy use decreases them. In addition, separate analyses for EU and non-EU members indicate that agricultural activity has a significant negative effect only for the non-EU countries, which is further discussed with some relevant empirical evidence. The approach utilizes three fields of policy action. Firstly, economic growth comes to the Union countries with a cost—carbon emissions. Policymaking needs to include strategies to turn growth into sustainable growth. Secondly, the magnitude of the impact of economic growth on carbon emissions is greater than the magnitude of the impact of renewable energy. Research and development efforts need to improve this situation. Thirdly, the use of appropriate tools and technologies can decrease the carbon footprint of agricultural activity.

Do Income Inequality and Institutional Quality affect CO2 Emissions in Developing Economies?

Concerns about income inequality and environmental pollution have stayed important aspects in reaching sustainable development objectives. However, economies continue to struggle with income inequality reduction and environmental degradation mitigation, all of which need significant consideration. Hence, the purpose of this research is to look into the relationship between income inequality, institutional quality, and carbon dioxide (CO₂) emissions in 42 developing countries from 1984 to 2016. Furthermore, the current study also investigates the role of institutional quality in moderating the relationship between income inequality and CO₂ emissions. For empirical analysis, we used cross section dependence, cross section unit root, and Westerlund's cointegration test to confirm the cross section dependence, stationarity, and cointegration among variables. Moreover, for long-run estimates, we employed Driscoll Kraay regression. According to the Driscoll Kraay regression outcomes, rising income inequality (without interaction term) leads to rising CO₂ emissions. However, (with interaction term) it shows a significant negative effect on CO₂ emissions. The findings of the interaction term (LnISQXLnINE) disclose a significant negative effect on CO₂. Moreover, an increase in institutional quality, economic development, energy consumption, industrialization, and trade openness significantly increase CO₂ emissions in all the models. In addition, the square term of income inequality and economic growth depicts an inverted U-shaped association with CO₂ emissions. The outcomes are also verified by the robustness check results acquired employing the fully modified ordinary least squares (FMOLS) and pooled mean group (PMG). Furthermore, Dumitrescu and Hurlin's panel causal test reveals a bidirectional causality running from income equality, energy consumption, industrialization, economic growth, trade, and interaction term toward CO₂ emissions. In view of the sustainable development goals (SDGs), the findings proposed significant policy repercussions for the study's sample economies.

The role of innovations and renewable energy consumption in reducing environmental degradation in OECD countries: an investigation for Innovation Claudia Curve

Rising economic growth in recent ages is the primary concern of most of the countries to enhance the living standard, but the ever-increasing production of economic activities consumes a lot of energy, which leads to a sharp increase in carbon dioxide emissions. Innovation may be a remedy that can help improve energy efficiency, obtain renewable energy, and promote economic growth, thereby protecting the quality of the environment. Therefore, this paper examines the role of innovation and renewable energy consumption in CO2 reduction in OECD countries from 2004 to 2019. By using the two-step system generalized of moment estimator, the results show that economic growth and innovation significantly increase carbon emissions, however the innovation Claudia Curve (ICC) is verified, and the environmental Kuznets curve does not exist. Foreign direct investment has a negative impact on carbon emissions, thus verifying the Pollution Hao hypothesis, whereas renewable energy also improves environmental quality, but the interaction between innovation and renewable energy consumption still increases carbon emissions. Financial development, industrialization, trade, and energy consumption have also been found to be harmful factors of environmental quality. Our findings have considerable policy implications for OECD countries on the improvement of innovation indicators and investment in renewable energy sources to rise environmental quality.

Exploring the nexus between environment quality, economic development and industrialization in BRICS nations: the role of technological innovation and income inequality

From the last few decades, the issue of sustainability of the growth process has become the prime objective for most economies. The quality of the environment contributes significantly to achieving the objective of sustainability of the growth process. Therefore, in recent years, the policy of world economies increases its emphasis on growth, prosperity, and opportunities for all with a clean environment. Keeping in this mind, in the present paper, we examined the impact of income, technological innovation, income inequality, and industrialization on the environment quality in Brazil, Russia, India, China, and South Africa (BRICS) during the period 1996-2016. The results display cross-sectional dependency within the panel of BRICS nations. Westerlund's cointegration test verifies a long-run relationship between the concerned variables. The dynamic ordinary least square method (DOLS) exhibits that technological innovation has negative while industrialization has a positive impact on the degradation of environmental quality. The results support the existence of the environment Kuznets curve (EKC) to per capita gross domestic product (GDP). Additionally, the paper evaluates the causal link between the variables by using the Dumitrescu-Hurlin panel causality test, and the outcomes support the existence of feedback hypothesis between environmental quality and GDP per capita, and between environmental quality and income inequality. Based on the findings, innovation-driven industrialization and development with equitable distribution of income can help these economies to attain the objective of sustainability of the growth process.