Are the impacts of renewable energy use on load capacity factors homogeneous for developed and developing nations? Evidence from the G7 and E7 nations

Spatio-temporal investigation of economic growth and environmental quality nexus in EU countries: New guidelines regarding green goods and eco-tax

The issue of environmental degradation has become pertinent and the call for carbon neutrality has intensified in recent years. Achieving this target will require countries to meet the conditions of the sustainable development goals. To do this, the study applied spatiotemporal modelling and the generalized method of moments (GMM) to examine the nexus between economic growth (EG) and the load capacity factor (LCF) through environmental goods (ENG) and environmental tax (ENT) among European Union (EU) nations from 1995 to 2018. The findings demonstrate that spatial dependence leads to a change in EG and LCF that impacts the EG and LCF of the neighbouring countries. The study also found that there is a significant positive and bidirectional relationship between economic growth and load capacity factor. Moreover, the study revealed that a positive effect of ENG, ENT, REN and Human Capital Index (HCI) on EG, with a reducing effect from natural resource rents (NRR). Finally, HCI improves environmental quality, while ENG, ENT, REN and NRR degrade the environment. Our findings justify the need for EU countries and other developed nations to implement policies that will help achieve a green economic transformation.

Do circular economy, renewable energy, industrialization, and globalization influence environmental indicators in belt and road initiative countries?

This paper is the first comprehensive research to examine the effect of circular economy on environment employing two environmental degradation indicators (CO2 emissions, ecological footprint) and one environmental quality indicator (load capacity factor) for 57 Belt and Road Initiative (BRI) countries during 2000-2019. The effect of other variables such as renewable energy, industrialization, and globalization was also controlled. The study applied the cross-sectional autoregressive distributed lag method (CS-ARDL), the augmented mean group (AMG), and common correlated effects mean group (CCEMG) methods as a robustness checks. The empirical findings reveal that circular economy and renewable energy have pro-environmental effects by decreasing carbon emissions and ecological footprint and increasing the load capacity factor in BRI countries. However, industrialization and globalization have detrimental effects on the environment. The result of causality shows a bidirectional causality between renewable energy, circular economy, industrialization, and three environmental indicators, but the relationship of globalization with CO2 emissions and the load capacity factor is unidirectional and with the ecological footprint is bidirectional. All the results are confirmed by the robustness tests. The study suggests policy implications for the BRI government.

Trade openness, human capital, natural resource, and carbon emission nexus: a CS-ARDL assessment for Central Asian economies

There is a call for global efforts to preserve the ecological systems that can sustain economies and people's lives. However, carbon emission (CEM) threatens the sustainability of humanity and ecological systems. This analysis looked into the influence of energy use (ERU), human capital (HCI), trade openness (TOP), natural resource (NRR), population, and economic growth (ENG) on CEM. The paper gathered panel data from the Central Asia region from 1990 to 2020. The CS-ARDL was applied to establish the long-term interaction among the indicators. The paper's findings indicated the presence of the environmental Kuznets curve (EKC) in the Central Asia regions. Also, the empirical evidence highlighted that energy use, natural resources, and trade openness cause higher levels of CEM. However, the research verified that CEM can be improved through human capital and urban population growth. The study also found that HCI moderates the interaction between NRR and CEM. The causality assessment indicated a one-way interplay between ENG, ERU, NRR, and CEM. The study proposes that to support ecological stability in these regions, policy-makers should concentrate on developing human capital, investing in renewable energy sources, and utilizing contemporary technologies to harness natural resources in the economies of Central Asia.

Reinvigorating the environmental Kuznets curve hypothesis in the context of highly polluted nations: evidence using advanced panel estimation techniques

China, United States, India, Russia, and Japan are regarded as the top five carbon dioxide-emitting nations in the world. These countries altogether account for more than half of the global annual discharges of carbon dioxide. Consequently, impeding the carbon emission-led environmental adversities in these countries is of critical emphasis for establishing environmental sustainability worldwide. In this regard, this study checks how economic progress, energy use intensification, and renewable energy use affect the annual growth rates of per capita carbon dioxide emission in these highly-polluted economies considering the study period from 1990 to 2021. Besides, for analytical purposes, advanced panel data estimation techniques have been utilized for detecting and neutralizing the impacts of cross-sectional dependency and slope heterogeneity-related problems in the data. Overall, the findings endorse that economic progress deteriorates environmental quality both in the short and long run. However, since the long-run unfavorable environmental impacts of economic growth are relatively lower compared with the short-run impacts, the environmental Kuznets curve hypothesis can be deemed valid. Besides, more intensive use of energy resources is witnessed to impose negative long-run environmental consequences while the adoption of renewable energy instead of fossil fuels is found to improve environmental well-being, both in the short and long run. Furthermore, the results affirm that economic progress and energy use intensification jointly degrade environmental conditions. By contrast, economic progress alongside greater adoption of renewable energy is observed to inflict an environmental quality-improving effect. Considering these findings, a couple of carbon dioxide mitigating policies are suggested to the concerned highly polluted developed and developing nations.

Investigating the fishing grounds load capacity curve in G7 nations: Evaluating the influence of human capital and renewable energy use

This paper introduces a novel approach to explore marine ecosystem by examining the Fishing Grounds Load Capacity Curve (FGLCC) hypothesis. The study investigates the impact of income on the marine condition in G7 nations from 1970 to 2019 by exploring the U-shaped relationship between income and the Fishing Grounds Load Capacity Factor (FGLCF). This research diverges from previous studies focused solely on the demand side through fishing footprints, as it considers the neglected aspect of the marine supply side. Furthermore, it explores the influence of renewable energies and human capital as indicators inversely related to non-renewable energy use and population on the marine condition. The findings reveal the U-shaped FGLCC hypothesis. Additionally, the results demonstrate that renewable energies and human capital have a positive impact on the marine ecosystem. These outcomes provide valuable insights for decision-makers, enabling them to identify key variables that contribute to the preservation of marine diversity.