A Roadmap toward Achieving Sustainable Environment: Evaluating the Impact of Technological Innovation and Globalization on Load Capacity Factor

Evaluating the effects of ECON-ESG on load capacity factor in G7 countries

For the first time, this study introduces the ECON-ESG quadruple, developed by Işık et al. (2024a), by adding the economy (ECON) dimension to the classical ESG (environment, social, governance) triad. Based on this new concept, it explores the impact of ECON-ESG factors on the Load Capacity Factor (LCF) in G7. The impact of ECON-ESG factors on LCF is vital because sustainability through these factors plays a critical role in a sustainable environment with LCF. CS-ARDL model finds that while governance factors (GOVNF) positively affect LCF, economic factors (ECONF) have negative effects. Environmental factors (ENVF) and social factors (SOCF) do not affect LCF. These findings can be interpreted as follows: (i) Negative effects of ECONF on LCF can be interpreted as high productivity levels in G7 leading to high resource consumption, exceeding biocapacity. (ii) In G7 with high-income levels, increased consumption may lead to overconsumption of natural resources and exceeding biocapacity. (iii) High technological progress in G7 can sometimes paradoxically lead to greater resource consumption rather than encouraging more efficient resource use, increasing an ecological footprint. The positive effects of GOVNF on LCF can be interpreted as follows: (iv) High and quality governance practices and policies in G7 can increase biocapacity. (vi) Under good governance, governments and environmental organizations can positively impact LCF by raising public awareness of environmental issues and enabling society to use natural resources more sustainably. Therefore, policymakers should harmonize economic policies through ECONF and governance policies through social factors (GOVNF), which contradict each other in LCF. Additionally, the effect of the single composite form ECON-ESG introduced and proposed in this study on LCF is found to be negative. This requires policymakers and firms to re-evaluate their sustainability one more time from a holistic perspective, including economic factors, as done in this study.

Environmental regulation, land use efficiency and industrial structure upgrading: Test analysis based on spatial durbin model and threshold effect

Environmental regulation promotes industrial structure change and regional economic transformation through land use adjustment, which gets a new way to explore the path of reforming traditional industrialization and urbanization. Based on the panel data of 128 prefecture-level cities in China 's Yangtze River Economic Belt from 2000 to 2020, this paper uses the spatial Dubin model to analyze the impact of environmental regulation and land use efficiency on the upgrading of industrial structure, and sets the panel threshold model to examine the impact of environmental regulation on the upgrading of industrial structure by affecting land use efficiency. The results show that formal environmental regulation has a significant positive spatial effect on the rationalization and upgrading of industrial structure, which are 0.1734 and 0.2854 respectively. Informal environmental regulation has a negative spillover effect on neighboring provinces but not significant. Heterogeneous environmental regulation has obvious "double threshold effect" on industrial upgrading by affecting land use efficiency. When the threshold of environmental regulation intensity is 0.0315-0.0886, environmental regulation still inhibits land use efficiency and industrial structure upgrading. When the threshold value is greater than 0.0886, environmental regulation has a positive impact on land use efficiency but not significant. With the intensity of environmental regulation from weak to strong, it will produce a double threshold effect of "strong inhibition-weak inhibition-interaction promotion" on the upgrading of manufacturing structure through the adjustment of land use efficiency.

Do renewable energy and human capital facilitate the improvement of environmental quality in the United States? A new perspective on environmental issues with the load capacity factor

Recently, countries have been making intensive efforts to alleviate the burden on the environment and to make environmental conditions sustainable. In this context, our study aims to investigate the long-term impact of renewable energy consumption (REC) and human capital (HC) by considering the load capacity factor (LCF). We also investigate the long-term impact of economic growth (Y) and non-renewable energy consumption (NREC) on the LCF. In this context, we analyze annual data for the U.S. for the period 1965-2018 using the newly developed augmented ARDL (AARDL) approach. The long-term empirical results show the following. i) Increases in Y negatively affect LCF and deteriorate environmental quality. ii) Increases in NREC negatively affect LCF and accelerate the deterioration of environmental quality. iii) REC has no significant impact on environmental quality. iv) Increases in HC support the improvement of environmental quality. The empirical results show that contrary to expectations, renewable energy consumption does not have a significant impact on environmental quality in the U.S., whereas human capital is an important factor in improving environmental quality. In this context, US policymakers should pave the way for more investment in eco-friendly renewable energy investments and human capital to establish sustainable environmental quality. Policymakers should also take steps to reduce the use of fossil fuels.

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.

The role of environmental technologies, institutional quality, and globalization on environmental sustainability in European Union countries: new evidence from advanced panel data estimations

Factors such as investments in environmentally clean technologies, globalization, and institutional quality significantly increase environmental quality. The study aims to provide light on how environmental technologies, institutional quality, globalization, and economic growth affect a sustainable environment. In addition, this study evaluates the European Union's carbon zero target by 2050 and the results of achieving carbon neutrality by 2030, which was put on the agenda at the UN Climate Change Conference of the Parties (COP-26). For this purpose, ten countries (Germany, Austria, Denmark, Finland, France, Netherlands, Spain, Italy, Sweden, and Switzerland) that invest in the highest environmental technology in the European Union were selected in the study. The data range of the study is from 1990 to 2019. Also, the validity of the load capacity curve (LCC) hypothesis was investigated in these countries. The CCEMG and DCCE estimators were used to estimate long-run coefficients. When the panel was assessed as a whole, the LCC hypothesis was determined to be valid by both estimators. According to country-based results, it has been determined that the LCC hypothesis is valid only for Spain. The study also includes the following observations. (i) Environmental technologies increase LCF for Austria, improving environmental quality. (ii) Globalization reduces LCF for Austria. (iii) Institutional quality variable decreases LCF for Austria and increases LCF for Germany and France. These findings suggest that to attain a sustainable environment in the future, policymakers should raise research and development budgets for environmental technology, enhance the standards of institutions, and take globalization into account.

Evaluating the impact of technological innovation and energy efficiency on load capacity factor: empirical analysis of India

The determinants of environmental degradation have been investigated many times by utilizing carbon dioxide emissions and/or ecological footprint. However, these traditional environmental degradation indicators do not consider the supply side of environmental problems. Therefore, this study focuses on the dynamic influence of financial development, energy efficiency, economic growth, and technological innovation on environmental degradation in India through the load capacity factor, including both the supply and demand sides of environmental problems. For that purpose, the recently developed dynamically simulated autoregressive distributed lag (ARDL) method is employed using the annual time-series data extending from 1980-2020. The dynamically simulated ARDL results demonstrate that financial development, economic growth, and technological innovation have a dynamic adverse impact on the load capacity factor, whereas energy efficiency has a positive dynamic influence on environmental quality. In addition, the results support the validity of the environmental Kuznets curve hypothesis as the negative effect of economic growth on environmental quality decreases over time. Based on the study findings, policy recommendations are provided for India. Finally, this study utilizing load capacity factor as an indicator for environmental quality will provide new topics in exploring the determinants of environmental degradation.

Sustaining environment through municipal solid waste: evidence from European Union economies

As part of their pursuit to succeed the Sustainable Development Goals (SDGs), European Union (EU) countries have placed great importance on realizing SDG 11, which aims to create sustainable cities and communities. The relationship between environmental quality and municipal solid waste remains understudied despite its significant impact on achieving SDG-11. Consequently, this study seeks to peruse municipal solid waste, renewable energy consumption, human capital, and natural resources impact on load capacity as a comprehensive measure of environmental quality. By utilizing the CS-ARDL approach, this study reveals the inadequacy of municipal solid waste conversion in EU countries and highlights the favorable effect of human capital and renewable energy on enhancing environmental quality. Moreover, this study provides concrete evidence that natural resources contribute to environmental corruption. EU economies should adopt policies to bolster municipal solid waste conversion to improve environmental quality.

How military spending, economic growth, and renewable energy impacts ecological footprints in Next Eleven nations

The objective of this study is to investigate the association between military spending and environmental sustainability within the N-11 countries. There exists a strong correlation between sustainable economic expansion and energy consumption, which in turn results in the generation of elevated levels of carbon emissions. Moreover, it is plausible that a correlation exists between military spending and the degradation of the environment. The primary objective of this study is to examine the emissions of carbon and emissions of greenhouse gases in the N-11 countries, as these nations exhibit comparatively elevated levels of such emissions. Therefore, this study examines the correlation among economic growth, militarization, renewable energy, and environment in the Next Eleven nations from 1990 to 2022. The cross-section autoregressive distributed lag (CS-ARDL) model is employed to analyze the enduring and immediate connections between variables. Empirical evidence indicates that a country's environment is positively influenced by GDP and militarization. The escalation of military capital intensity has exacerbated the environmental damage. Increasing the adoption of renewable energy sources can mitigate negative environmental impacts over time. This study proposes policy recommendations for sustainable development, including reducing militarization and improving the use of clean energy.

Impact of banking development and renewable energy consumption on environmental sustainability in Germany: Novel findings using the bootstrap ARDL approach

This study examines the effects of banking development, economic growth and consumption of renewable energy on carbon dioxide (CO2) emissions and load capacity factor (LCF). Previous empirical studies have assessed the interrelationship between banking development and CO2 emissions; however, these studies have ignored supply-side ecological issues. To overcome this issue, this study evaluates the effect of banking development on LCF, which is considered to be one of the most comprehensive ecological proxies to date, including both biocapacity and ecological footprint (EF). Using the bootstrap autoregressive distributed lag model, the study reveals that renewable energy improves ecological quality in Germany. The results of the investigation demonstrate that the environmental Kuznets curve hypothesis is valid in Germany using CO2 emissions and LCF indicators. Furthermore, this study demonstrates that banking growth and renewable energy in Germany correlate with improved environmental quality. These findings provide policymakers with important insights. In this context, the study advises the banking industry and government authorities to leverage banking expansion to support green energy to achieve the national goal of zero CO2 emissions by 2045.

In the era of globalization, can renewable energy and eco-innovation be viable for environmental sustainability in BRICS economies?

Although energy is a necessary component of production and hence a contaminant, the environmental effect varies depending on the type of energy used. Renewable sources of energy can provide ecological advantages, particularly when contrasted with fossil fuels, which emit high levels of CO2 emissions. Thus, the research explores the impact of eco-innovation (ECO), green energy (REC), and globalization (GLOB) on the ecological footprint (ECF) in the BRICS nations using the panel nonlinear autoregressive distributed lag (PNARDL) technique between 1990 and 2018. The empirical results indicate that there is cointegration in the model. The results from the PNARDL show that a positive shift in renewable energy, eco-innovation, and globalization decreases the ecological footprint, while positive (negative) shifts in non-renewable energy and economic growth intensify the ecological footprint. The paper suggests several policy recommendations based on these results.

How do natural resources and economic growth impact load capacity factor in selected Next-11 countries? Assessing the role of digitalization and government stability

With growing  environmental concerns, everyone's attention has shifted to how we use our limited materials supplies. Rapid economic expansion is dependent on heavy resource use, decreasing biodiversity and raising the ecological footprints (EF), resulting in a reduction in the load capacity factor (LCF). Because of this, scholars and policymakers are actively looking for approaches to improve the LCF without hindering economic growth (GDP). For similar reasons, this research aims at how the selected next eleven economies improved their LCF from 1990 to 2018 by analyzing the effect of digitalization (DIG), natural resources (NAT), GDP, globalization, and governance. To account for dependence across sections and slope variation, the cross-sectional augmented ARDL model is used in this research. The long-term findings indicate that LCF was diminished by dependence on NAT, globalization, and economic growth and was bolstered by DIG and sound governance. The work recommends that financial and policy support is needed for initiatives such as zero-emission vehicle production and energy-efficient building construction. By offering a line of credit at low interest rates, renewable energy projects can attract domestic and private investors.

Analyzing the validity of load capability curve: how economic complexity, renewable energy, R&D, and communication technologies take their part in G-20 countries

Intense anthropogenic contamination of the air, water, and soil inspires scholars to examine the causes of pollution and provide remedies to assure environmental sustainability. Therefore, researchers in this study are driven to investigate the causes of the severe air, water, and soil contamination that has resulted from human activity and to offer recommendations for achieving environmental sustainability. This research contributes to the ecological works by suggesting the load capability curve (LCH) hypothesis and using the load capacity factor (LC) to investigate components influencing climatic quality. The LC enables thorough climatic value examination when comparing ecological footprint and biocapacity. Information and communication technologies (INF), development and research (R&D), renewable energy (RE) usage, and disposable income are all examined, considering their effects on the load capacity factor. This analysis utilizes the cross-sectionally augmented autoregressive distributed lag estimator and the Westerlund cointegration on data for the G-20 countries from 1995 to 2018. Empirical evidence suggests that renewables, R&D spending, economic complexity, and INF all benefit environmental quality. This study cannot support the LCH hypothesis, which states that increasing income worsens ecological conditions up to a certain point but then aids in improving environmental quality afterward. Based on the findings, G-20 governments should prioritize environmental policies that boost economic growth, spread renewable energy, prioritize research and development spending, and assist the implementation of green INF infrastructure.

The effects of trade, renewable energy, and financial development on consumption-based carbon emissions (comparative policy analysis for the G20 and European Union countries)

Recently, there has been a lot of focus on global trade and consumption-based carbon (CCO2) emissions. More research, however, has examined how financial development (FD) and international trade in renewable energy affect CO2 emissions. Furthermore, there are no distinct trends in the research about how globalization affects environmental quality. Our research analyzes and empirically investigates the relationship between CCO2 emissions and renewable energy, FD, and trade. A large panel of data from 41 G20 and European Union (EU) countries is assembled for empirical analysis from 1990 to 2019. The practical outcomes of panel quantile regression and feasible generalized least square (FGLS) approaches display that renewable energy and FD positively relate to CCO2 emissions; furthermore, trade to GDP hurts CCO2 emissions; market classification has been taken as a control variable which shows that the developed countries released more carbon than non-developed countries. These results suggest that the financial sector focuses more on supporting companies that use ecologically friendly techniques and pushing them to use other energy well-organized technologies in their production processes. As a result, CCO2 emissions will be reduced, preventing environmental damage at the non-renewable energy plant.

Evaluating the impact of digitalization, renewable energy use, and technological innovation on load capacity factor in G8 nations

Ecosystems are in danger due to human-caused air, water, and soil pollution, so it is important to find the underlying causes of this issue and develop practical solutions. This study adds to environmental research gap by suggesting the load capability factor (LCF) and using it to look at the factors affectting environmental health. The load capacity factor simplifies monitoring environmental health by illustrating the distinction between ecological footprint and biocapacity. We examine the interplay between mobile phone users (Digitalization DIG), technological advancements (TEC), renewable energy use, economic growth, and financial development. This study assesses G8 economies' data from 1990 to 2018, using a Cross-Section Improved Autoregressive Distributed Lag CS-ARDL estimator and a cointegration test. The data shows that green energy, TEC innovation, and DIG are all beneficial for natural health. Based on the results of this study, the G8 governments should focus on environmental policies that promote economic growth, increase the use of renewable energy sources, guide technological progress in key areas, and encourage the development of digital information and communications technologies that are better for the environment.

Assessing the role of the insurance market and renewable energy in the load capacity factor of OECD countries

In the empirical literature, few studies assessed the influence of the insurance market on carbon emissions. However, the effects of insurance markets on the load capacity factor (LCF) have been ignored. In this regard, the objective of the current work is to assess the potential impact of the insurance market on environmental sustainability in 27 OECD countries from 1990 to 2018 based on the LCF, which implies the strength of a state to enhance the population based on the current lifestyle. The present work employed the novel Method of Moments Quantile Regression (MMQR). This model is the prime and correct technique to better understand the association between the insurance market and the LCF across heterogeneous quantiles and to yield more robust empirical outcomes. The MMQR findings indicate a negative interaction between the insurance market and the LCF. In other words, the insurance sector has a powerful influence on economic activities and investments, such that insurance activities lead to an increase in the level of energy utilization, and thus have a negative influence on ecological sustainability. In contrast, the findings illustrate a positive and considerable association between renewable energy consumption and LCF. Based on the overall outcomes, it is suggested that OECD countries should focus on policies that encourage the use of renewable energy rather than incentivizing the insurance market. OECD country governments should also support green insurance activities to minimize the environmental damage of the insurance market.

Effect of green bonds, oil prices, and COVID-19 on industrial CO2 emissions in the USA: Evidence from novel wavelet local multiple correlation approach

This study explores the effect of green bonds, oil prices, and the coronavirus disease 2019 (COVID-19) pandemic on industrial carbon dioxide (CO2) emissions. In this context, this study examines the United States of America (USA), which is the biggest economy in the world, uses weekly data between March 6, 2020 and September 30, 2022, and applies a novel wavelet local multiple correlation (WLMC) approach under time-varying and frequency-varying perspective. The novel empirical findings shows that (i) there is a strong negative (positive) co-movement between industrial CO2 emissions and green bonds in the short-run (long-run); (ii) there is a strong positive (negative) co-movement between industrial CO2 emissions and oil price in the medium-run (long-run); (iii) there is a strong negative (positive) co-movement between industrial CO2 emissions and the COVID-19 pandemic in the medium-run (long-run); (iv) the oil price is the dominant factor, whereas there are changing effect of the variables on each other at different times and frequencies; and (vi) overall, there are long-run asymmetric and dynamic correlations between industrial CO2 emissions and variables. Hence, the empirical results highlight the asymmetric, time-varying, and frequency-varying effects of green bonds, oil prices, and the COVID-19 pandemic on industrial CO2 emissions by presenting fresh and novel evidence. Moreover, the study proposes policy implications for the USA government.

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

Both developed and underdeveloped economies worldwide are now more concerned than ever in respect of achieving environmental sustainability. Accordingly, the majority of the global economies have ratified several environment-related pacts to facilitate the tackling of global environment-related problems. Although these problems are assumed to be addressed using diverse mechanisms, limiting the use of fossil fuels has often been recognized as the ultimate enabler of environmental sustainability. Against this backdrop, this study aims to assess the environmental impacts associated with higher renewable energy use, controlling for economic growth and population size, in the context of the G7 and E7 countries using data from 1997 to 2018. Moreover, instead of using the traditional environmental quality proxies, this study tries to proxy environmental degradation with the load capacity factor levels of the countries of concern. The long-run associations among the study's variables are confirmed by outcomes generated from the cointegration analysis. Besides, regression analysis highlighted that integrating renewable energy into the energy systems while withdrawing from the use of fossil fuels can help to improve environmental quality by increasing the load capacity factor levels. In contrast, economic growth and population size expansion are evidenced to impose environmental quality-dampening impacts by reducing the load capacity factor levels. However, the findings, in the majority of the cases, are seen to differ across the groups of the G7 and E7 countries, especially in terms of the variations in the magnitudes of marginal environmental effects over the short and long run. Lastly, the causality analysis confirms the directions of the causal relationships among the variables of concern. Based on these results, a couple of policy interventions are recommended for improving environmental quality in the G7 and E7 countries.

Role of energy consumption and trade openness towards environmental sustainability in Turkey

The growth of financial services has been critical in Turkey's pursuit of economic growth objectives throughout the last two decades. Nevertheless, it cannot be denied that it has a negative impact on environmental quality. Based on this, in the current paper, the effect of energy use, trade openness, and financial development on the load capacity factor (LCF) is explored for Turkey between 1965 and 2018. In doing so, a series of quantile approaches such as quantile cointegration (QC), quantile-on-quantile regression (QQR), nonparametric causality-in-quantiles (NCQ), and quantile regression (QR) are used. The results generated from the QQR and also validated by the QR reveal that in the majority of the quantiles, primary energy use, trade openness, and financial development impact the LCF negatively. These results suggest that primary energy use, trade openness, and financial development damage environmental quality. Furthermore, the findings gathered from the quantile causality disclose that all primary energy use, trade openness, and financial development can forecast LCF in the majority of the quantiles. Based on the research outcomes, policies, which may aid to solve the damaging environmental effects of the primary energy use, trade openness, and financial sector development in Turkey are recommended.

Race to achieving sustainable environment in China: Can financial globalization and renewable energy consumption help meet this stride?

Investigating the drivers of CO2 emissions is essential for limiting global warming, which has sparked widespread concern. This study evaluates the association between economic complexity and CO2 emissions in China, considering the effect of disintegrated energy and financial globalization on the environmental function between 1970 and 2018. This dataset was analyzed using the autoregressive lag model (ARDL) and frequency-domain causality approaches. The ARDL unveiled that urbanization, economic complexity, financial globalization, and economic growth deteriorate the environment while environmental sustainability is achieved through renewable energy utilization. The study also validates the Environmental Kuznets Curve hypothesis. Also, the frequency-domain causality disclosed that all regressors (economic growth, financial globalization, economic complexity, and urbanization) could forecast CO2 emissions in China at different frequencies. Based on these outcomes, policy recommendations are formulated.