Globalization and renewable energy use: how are they contributing to upsurge the CO2 emissions? A global perspective

Bio-inspired computational intelligence metaheuristic-based optimization and sensitivity analysis approach to determine techno-economic feasibility of hydrogen refueling stations for fuel cell vehicles

This study presents a comprehensive economic and technological evaluation of renewable hybrid power systems for hydrogen refueling stations (HRS) in Nizwa, Oman, leveraging cutting-edge optimization algorithms to determine the most cost-effective and efficient hybrid energy system configurations. Three hybrid energy systems of photovoltaic-wind turbine-battery (PV-WT-B), photovoltaic-wind-fuel cell-battery (PV-WT-FC-B), and wind turbine-battery (WT-B) were evaluated based on net present cost (NPC), levelized cost of energy (LCOE), and levelized cost of hydrogen (LCOH). The study employs advanced optimization techniques, including the Mayfly Algorithm, Genetic Algorithm, CUKO Search, Gray Wolf Optimizer (GWO), Constrained Particle Swarm Optimization (CPSO), Harmony Search (HS), and Flower Pollination Algorithm to determine the most viable hybrid energy system for the HRS in Nizwa. The results indicate that CPSO consistently achieves the lowest NPC, LCOE, and LCOH, whereas HS and GWO yield higher costs due to convergence inefficiencies. Sensitivity analysis reveals a strong inverse correlation between PV capacity and cost metrics, highlighting the economic advantage of increased solar generation. Additionally, hybrid configurations integrating PV and wind turbine (PV-WT-B, PV-WT-FC-B) significantly reduce NPC compared to WT-B, reinforcing the role of solar energy in optimizing economic costs. Furthermore, fuel cell integration (PV-WT-FC-B) imposes additional economic burdens, making PV-WT-B the most viable solution for HRS deployment in Oman. More so, the annual worth and return-on-investment analysis demonstrated that the PV-WT-B is the preferred energy system to meet the needs of the HRS in terms of investment. The findings underscore the importance of renewable energy fraction and capacity factor in energy economics, demonstrating that higher PV integration enhances sustainability and cost-efficiency. This study provides a transformative framework for decarbonizing Oman's transportation sector, offering insights into optimal hydrogen production strategies to advance the global clean energy transition.

Sustainable tourism for climate change and environmental sustainability in Tunisia: Evidence from a novel measure, nonlinear modeling, and wavelet coherence

This study examines the asymmetric impact of international tourism on CO2 emissions and environmental sustainability in Tunisia. Using the Nonlinear Autoregressive Distributed Lag (NARDL) model within a Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework, we construct a composite index via Principal Component Analysis (PCA). Robustness checks include Fully Modified Ordinary Least Squares (FMOLS), Bias-corrected Wavelet coherence, and asymmetric causality analysis through Vector Autoregression (VAR). Findings reveal that tourism traffic asymmetrically affects environmental sustainability, except for carbon emissions, even under nonlinear Granger causality analysis. Trade openness also exerts asymmetric effects, supporting the Pollution Haven hypothesis. Policy recommendations highlight the need for smart strategies such as mobile applications and taxation to track tourism-related carbon footprints, foster youth-led tourism businesses, address brain drain, and advance a circular economy. Sustainable tourism, alongside key structural factors, plays a vital role in shaping long-term environmental quality. Strategic agricultural development, improved governance, and the efficient use of renewable energy are crucial. Enhancing energy security, reducing fossil fuel dependence, and promoting green technology investments are necessary steps. This study contributes uniquely by compiling and updating a dataset based on six environmental criteria-air quality, energy management, biodiversity, health, population pressure, and water resources-while employing advanced econometric techniques.

Sustainable Formate Production via Highly Active CO2 Hydrogenation Using Porous Organometallic Polymer with Ru-PNP Active Sites

Efforts to combine the advantages of homogeneous catalysts in terms of activity with the ease of separation process offered by heterogeneous catalysts continue to be actively pursued in the field of catalyst development. Heterogeneous catalysts were synthesized from Ru-MACHO organometallic compounds, recognized for their high hydrogenation catalytic activity linked to the active site of the Ru-PNP motif, through direct polymerization utilizing the Friedel-Crafts reaction. These catalysts were then applied for the conversion of greenhouse gas carbon dioxide (CO2) into formate via hydrogenation, exhibited with a record-high turnover frequency of 31,700 and a productivity of 36,100 kgformate/(kgcatalyst ⋅ d). Furthermore, the facile separation characteristics and recyclability of the heterogeneous catalysts were confirmed.

Linear and non-linear impact of key agricultural components on greenhouse gas emissions

Agriculture significantly impacts the global environment, contributing to greenhouse gas (GHG) emissions, air and water pollution, and biodiversity loss. As the global population grows and demands higher agricultural output, these environmental impacts are expected to intensify. Among global contributors, China, with its vast population and prominent agricultural sector, plays a leading role in GHG emissions. Understanding and mitigating these impacts in China is crucial for addressing broader global environmental challenges. To address these key issues, we conducted a study on the dynamic impact of agricultural key variables (agricultural land, fertilizer consumption, energy use for agriculture, agricultural value-added, forest land, livestock, fisheries, and crop production) on GHG emissions by utilizing the data from 1990 to 2020, and employed linear and non-linear linear autoregressive distributed lag (ARDL and NARDL) models. In the study, co-integration analysis confirms the long-run relationship between variables, and the long-term findings from the ARDL model reveal important insights, increased agricultural land use, fertilizer consumption, agricultural energy use, crop production, livestock production, and fishery production increases GHG emissions in China and GHG emissions can be reduced by increasing forest land in the long term. Furthermore, with the asymmetric NARDL regression applied to three key variables, the positive shock analysis results confirm that agricultural land use (AGL+), fertilizer consumption (FC+), and agricultural energy use (EUA+) can significantly contribute to long-term GHG emissions. However, adverse shocks to (AGL-), (FC-), and (EUA-) could significantly compress GHG emissions. These findings offer valuable implications for Chinese authorities' focus on expanding forest land, using more renewable energy, and minimizing the usage of chemicals in agriculture. These measures can help to mitigate emissions while promoting sustainable agricultural practices.

Relationships between the Surface Hydrophilicity of a Bismuth Electrode and the Product Selectivity of Electrocatalytic CO2 Reduction

Two types of bismuth films (micro-Bi and nano-Bi) were prepared, and their electrocatalytic behavior was studied in terms of reduction current and product selectivity in a potential range of -0.776 to -1.376 V vs RHE. CO2 and H2O molecules competed with each other for reduction on the surfaces of both types of films, and formate and H2 were the respective major products of reductive reactions. Under the same conditions, nano-Bi exhibited lower selectivity for formate and higher selectivity for H2 compared to the respective micro-Bi cases with bismuth films of similar thickness. This can be attributed to the higher hydrophilicity of bismuth film surfaces of nano-Bi due to surface nanoscale roughness and lower surface-carbon content compared with those of micro-Bi. Our results suggest a new strategy for controlling the selectivity of electrocatalytic CO2 reduction under aqueous electrolytes through the use of surface engineering.

Gender empowerment and environmental impact: A quantile regression analysis in BRICS economies

This study, with its significant findings, delves into the impact of women's status on environmental quality in BRICS economies (Brazil, Russia, India, China, South Africa) from 1960 to 2022. Using a novel method, the Method of Moments Quantile Regression, this study has been able to analyse the relationship. The results, which are of utmost importance, show that women's political empowerment and leadership positions (government chief executives) significantly reduce carbon emissions, while the impact of women's civil liberties along with population growth increases emissions across the analysed quantiles. Economic growth is insignificantly negatively associated with environmental quality. The paper's findings reveal a unidirectional causal relationship from women's political empowerment to emissions, carbon emissions to women's civil liberties and emissions to economic growth. Additionally, a bi-directional causality connection is evident between population growth and environmental quality. These insights, which are crucial for policymaking, suggest that promoting improved women's status is a crucial policy strategy for mitigating climate change in BRICS economies. Thus, this paper suggests that empowerment of women is an effective strategy for reducing carbon emissions. It emphasizes the need for climate policy to promote gender equality, prioritise women's leadership in the clean energy industry, and enhance their access to resources and opportunities.

Uncovering the drivers of CO2 emissions in the United States: The hidden spillover effects

This study explores the applicability of the Environmental Kuznets Curve (EKC) hypothesis in the United States (US) from 2006 to 2020, employing the Spatial Durbin Model (SDM) to analyze the cross-border effects of pollution among states. The results indicate that although economic growth initially decreases environmental degradation, it subsequently contributes to more significant environmental degradation, challenging the EKC hypothesis's validity at the US state level. Factors such as higher energy prices and reliance on fossil fuels are also identified as significant drivers of environmental deterioration, with varying impacts observed across states. Conversely, adopting renewable energy sources is crucial in mitigating pollution levels. The study underscores the importance of coordinated state-level efforts to harmonize economic growth with sustainable environmental practices. It highlights the complexities of policymaking in balancing economic development with environmental conservation and emphasizes the need for targeted interventions to address environmental challenges effectively. This research enhances our understanding of sustainable development pathways amidst diverse regional dynamics within the US by providing empirical evidence and policy insights.

Balancing growth and sustainability: COP 28 policy implications of green energy, industrialization, foreign direct investment, and globalization in South Asia

This research investigates the intricate relationships between economic variables and how they affect South Asian nation's ability to develop sustainably. Given the growing concerns about climate change and global warming brought on by emissions of greenhouse gases, this study looks into the connection between emissions of CO2, green energy, industrialization, foreign direct investment, economic globalization, and financial development from 1995 to 2022. Second-generation panel techniques were employed in this study to look at the relationship between variables because of the potential of residual cross-sectional dependency and heterogeneity. The empirical outcomes display that green energy, economic globalization, and financial development reduce CO2 emissions by 1.839%, 1.223%, and 3.902% respectively. Industrialization and foreign direct investment degrade the environment by 4.302% and 1.893% respectively. A bidirectional causality link between green energy, industrialization, economic globalization, and CO2 emissions was found by Dumitrescu and Hurlin (D-H). Based on our findings, we recommend legislative support for renewable energy, cleaner technologies, and strict environmental regulations, aligning with the Sustainable Development Goals (SDGs). Encouraging FDI, sustainable practices, and financial development can drive economic growth while preserving the environment. As we approach COP28, this holistic approach to sustainable development becomes increasingly vital for South Asian countries to achieve their SDG targets and combat climate change.

Renewable energy, regional tourism, and exports to tackle stagnant growth in developed economies

This study examines the effects of energy resources in the form of clean and unclean energy on the economic progress of 30 selected developed economies. This study used data from 1990 to 2020 and it employs the CS-ARDL method to obtain results. The results present that both clean and unclean energy significantly stimulate economic progress. The findings further expose that foreign investment resources in the form of inflow are significant factors that accelerate economic progress in developed economies. The results reveal that tourism development, capital accumulation, and exports are significant factors in boosting economic progress in the selected economies. Estimates from Dumitrescu and Hurlin's method for heterogeneous panels confirm the presence of the feedback-effect hypothesis for unclean energy, while the energy-conservation hypothesis holds for clean energy. This study suggests that targeting low-cost clean energy production is crucial for promoting economic growth and protecting the environment through carbon mitigation strategies. There is also a need to develop a policy framework that emphasizes the transformation of industry towards clean energy at a macro level. Furthermore, transitioning from unclean to clean energy may enhance economic progress by improving environmental quality norms in the selected developed economies. Finally, policies for tourism development, export improvement, and increased inflow of FDI should be directed towards fostering clean energy agreements and achieving environment-friendly economic progress in developed economies.

Modelling energy trilemma and economic growth on renewables in N11 economies: Do economic complexity matter?

Utilizing renewable energy is a necessity for accomplishing global agendas, including combating climate change and promoting sustainable development programs. Although much literature has investigated the nexus between energy sources and their affected regressors during the last few years, no appreciable emphasis is available in the previous studies respecting the influence of the energy trilemma index and economic expansion on the influence of the energy trilemma index and economic the renewables in N11 economies. Therefore, the current study analyzes the crucial influencing factors, including the energy trilemma, economic growth, economic complexity, financial development, and urban population, as drivers of renewable energy in N11 economics from 1990 to 2021 by utilizing a panel quantile regression approach. The empirical outcomes certify that renewable energy is positively connected with the energy trilemma, economic growth, financial development, and urban population, but not with economic complexity, which has the inverse result. As a result, legislators responsible for monitoring the deployment of renewables should stimulate their attempts to consider the energy trilemma dimensions into account when determining energy structural policies, increase the use of greener energy subsidies, pose high-carbon taxes, promote green financial innovation, and improve energy efficiency.

Can forests realize the carbon neutrality dream? Evidence from a global sample

The enlarge in economic activities and the urban population at the global level has brought about an increase in the demand for energy, food, and natural resources, as well as an exacerbation in global climate change concerns. In this respect, it is important to ensure the balance between global climate change and global economic activities. Therefore, a wide literature has emerged that searches for alternative solutions to improve climate change and carbon dioxide (CO2) emissions. The majority of existing studies emphasize the importance of renewable energy sources in environmental improvement efforts. Few studies highlight the importance of forestation in environmental improvement efforts, highlighting the non-linear effects of forestation. To fill this gap, this study uses panel data from 181 countries between 1990 and 2022 and evaluates the non-linear impact of economic growth, forest extent, energy efficiency, and urban growth on per capita CO2 emissions using a dynamic panel threshold and dynamic panel quantile threshold methods. Furthermore, we extend the model and conduct robustness tests examining the non-linear threshold effects of renewable and non-renewable energy consumption on per capita CO2 emissions. Our findings provide pieces of evidence that forest extents are an alternative solution to renewable energy use and energy efficiency in environmental improvement efforts.

Renewable energy as a solution to climate change: Insights from a comprehensive study across nations

Without fundamentally altering how humans generate and utilise energy, there is no effective strategy to safeguard the environment. The motivation behind this study was to analyse the effectiveness of renewable energy in addressing climate change, as it is one of the most pressing global issues. This study involved the analysis of panel data covering 138 nations over a 27 year period, from 1995 to 2021, making it the latest addition to the existing literature. We examined the extent of the impact of renewable energy on carbon dioxide over time using panel, linear, and non-linear regression approaches. The results of our analysis, revealed that the majority of countries with the exception of Canada, exhibited a downward trend, underscoring the potential of increasing renewable energy consumption as an effective method to reduce carbon dioxide emissions and combat climate change. Furthermore, to reduce emissions and combat climate change, it is advisable for nations with the highest carbon dioxide emissions to adopt and successfully transition to renewable energy sources.

Assessing the spillover effects of various forms of energy on CO2 emissions - An empirical study based on dynamic spatial Durbin model

Previous studies ignored the geospatial dynamics spillover effects of energy consumption on CO2 emissions while assessing such impacts in developed and developing countries. Moreover, most studies wrongfully assess spillover effects in its aggregated format rather than decomposing by its components. This is important as not all energy sources share the same characteristics. We fill these gaps in the literature by investigating the spillover effects of various forms of energy, including fossil fuels, renewable energy, and nuclear power, on CO2 emissions in 135 developed and developing countries from 2000 to 2019. We used the Dynamic Spatial Durbin Model (DSDM) to better understand the results. A series of indicative tests confirmed using the DSDM model and including spatial interaction of CO2 emissions in the analysis. Our findings show evidence of indirect spillover effects of the various energy sources on CO2 emissions. Further considering the spillover effects of the energy sources of neighbouring countries, the paper finds that the driving increase in CO2 emissions mainly came from the energy consumption of the country itself and neighbouring countries' energy consumption. Nevertheless, the results indicate that the direct effects of energy consumption often exceed its indirect effects. The results also confirm that total and fossil energy consumption harms the environment, whereas adopting renewable and nuclear energy sources reduces CO2 emissions. Lastly, we find nuclear energy is the most environmentally sustainable energy source. The study concludes that the Dynamic Spatial Durbin Model is paramount in estimating the environmental impact of energy consumption in our sample. The practical policy implications drawn from this study could be used to promote increased collaboration to hasten the energy transition process and address global warming and climate change.

Revitalizing contaminated lands: A state-of-the-art review on the remediation of mine-tailings using phytoremediation and genomic approaches

The mining industry has historically served as a critical reservoir of essential raw materials driving global economic progress. Nevertheless, the consequential by-product known as mine tailings has consistently produced a substantial footprint of environmental contamination. With annual discharges of mine tailings surpassing 10 billion tons globally, the need for effective remediation strategies is more pressing than ever as traditional physical and chemical remediation techniques are hindered by their high costs and limited efficacy. Phytoremediation utilizing plants for remediation of polluted soil has developed as a promising and eco-friendly approach to addressing mine tailings contamination. Furthermore, sequencing of genomic DNA and transcribed RNA extracted from mine tailings presents a pivotal opportunity to provide critical supporting insights for activities directed towards the reconstruction of ecosystem functions on contaminated lands. This review explores the growing prominence of phytoremediation and metagenomics as an ecologically sustainable techniques for rehabilitating mine-tailings. The present study envisages that plant species such as Solidago chilensis, Festuca arundinacea, Lolium perenne, Polygonum capitatum, Pennisetum purpureum, Maireana brevifolia, Prosopis tamarugo etc. could be utilized for the remediation of mine-tailings. Furthermore, a critical evaluation of the organic and inorganic ammendments that optimize conditions for the remediation of mine tailings is also provided. The focus of this review extends to the exploration of environmental genomics to characterize microbial communities in mining sites. By delving into the multifaceted dimensions of phytoremediation and genomics for mine tailings, this study contributes to the ongoing efforts to revitalize contaminated lands for a sustainable and environmentally friendly future.

Role of energy transition in easing energy security risk and decreasing CO2 emissions: Disaggregated level evidence from the USA by quantile-based models

Consistent with the increasing environmental interest, the clean energy transition is highly critical to achieving decarbonization targets. Also, energy security has become an important topic under the shadow of the energy crisis,. Accordingly, countries have been trying to stimulate clean energy use to preserve the environment and ensure energy security. So, considering the leading role of economic size and volume of energy use, the study examines the USA to define whether energy transition helps decrease energy security risk (ESR) and curb CO2 emissions. So, the study applies a disaggregated level analysis by performing quantile-based models for the period from 2001/Q1 through 2022/Q4. The results demonstrate that (i) the energy transition index decreases environmental ESR at higher quantiles and reliability ESR at lower and middle quantiles, whereas it is not beneficial in declining economic and geopolitical ESR; (ii) energy transition curbs CO2 emissions in building and transport sectors at lower quantiles, whereas it does not help decrease CO2 emissions in industrial and power sectors; (iii) energy transition is mostly ineffective on ESR, whereas it is highly effective in curbing CO2 emissions in all sectors except for transport across various quantiles as time passes; (iv) the results differ according to the aggregated and disaggregated levels; (v) the results are consistent across main and alternative models. Hence, the study highlights the dominant effect of energy transition in curbing sectoral CO2 emissions rather than easing ESR. Accordingly, the study discusses various policy implications for the USA.

Impact of economic policy uncertainty and renewable energy on environmental quality: testing the LCC hypothesis for fast growing economies

This study investigates the influence of economic policy uncertainty and trade openness on load capacity factor for fast growing countries for time period of 1996-2019. The empirical outcomes verify the presence of the LCC hypothesis in fast growing economies. Results also show that economic policy uncertainty reduces environmental quality for lower quantiles, whereas renewable energy consumption is a useful tool for improving environmental quality. Moreover, the negative sign of the coefficient of trade openness demonstrates that the current pattern of trade is not providing the desired outcomes. Based on these empirical findings, we suggest a comprehensive policy framework to attain the targets of SDG 07 (renewable energy), SDG 08 (economic growth), and SDG 13 (climate action).

2D MXenes and their composites; design, synthesis, and environmental sensing applications

Novel 2D layered MXene materials were first reported in 2011 at Drexel University. MXenes are widely used in multidisciplinary applications due to their anomalous electrical conductivity, high surface area, and chemical, mechanical, and physical properties. This review summarises MXene synthesis and applications in environmental sensing. The first section describes different methods for MXene synthesis, including fluorinated and non-fluorinated methods. MXene's layered structure, surface terminal groups, and the space between layers significantly impact its properties. Different methods to separate different MXene layers are also discussed using various intercalation reagents and commercially synthesized MXene without compromising the environment. This review also explains the effect of MXene's surface functionalization on its characteristics. The second section of the review describes gas and pesticide sensing applications of Mxenes and its composites. Its good conductivity, surface functionalization with negatively charged groups, intrinsic chemical nature, and good mechanical stability make it a prominent material for room temperature sensing of environmental samples, such as polar and nonpolar gases, volatile organic compounds, and pesticides. This review will enhance the young scientists' knowledge of MXene-based materials and stimulate their diversity and hybrid conformation in environmental sensing applications.

An environmental perspective of energy consumption, overpopulation, and human capital barriers in South Asia

Prior literature is substantive in highlighting the nexus between pollutant and socio-economic predictors; however, the role of human interaction has not been sufficiently explored. Thus, the present study examines the validity of the environmental Kuznets Curve (EKC) hypothesis in the presence of energy consumption, overpopulation, and human capital index in five South Asian countries. It employs fixed effects, random effects, and dynamic panel causality techniques with a set of panel data from 1972 to 2021. The baseline results validate the existence of the EKC hypothesis in the recipient panel. Nevertheless, the findings reveal that energy consumption and population density have positive effects, while human capital has negative impacts on CO2 emissions. Furthermore, the study observes that energy consumption and per capita GDP have a significant causal link with CO2 emissions, whereas CO2 emissions are evident to have causality with population density and human capital index. The results are robust and suggest that the consolidation of an effective regulatory framework and technological improvements are substantial measures to improve environmental quality in South Asia. Moreover, allocating sufficient resources to uplift contemporary educational and health status would be imperative to improving environmental quality as aspired to by the Paris Agreement.

Unveiling the Quantitative Relationships between Electron Distribution and Steric Hindrance of Organic Amines and Their Reaction Rates with Carbonyl Sulfur: A Theoretical Calculation Investigation

The removal of carbonyl sulfide (COS) commonly contained in natural gas is of great significance but still very challenging via a widely employed absorption process due to its low reactivity and solubility in various commercial solvents. Artificial intelligence (AI) is playing an increasingly important role in the exploration of desulfurization solvents. However, practically feasible AI models still lack a thorough understanding of the reaction mechanisms. Machine learning (ML) models established on chemical mechanisms exhibit enhanced chemical interpretability and prediction performance. In this study, we constructed a series of solvent molecules with varying functional groups, including linear aliphatic amines, cyclic aliphatic amines, and aromatic amines and proposed a three-step reaction pathway to dissect the effects of charge and steric hindrance of different substituents on their reaction rates with COS. Chemical descriptors, based on electrostatic potential (ESP), average local ionization energy (ALIE) theory, Hirshfeld charges, and Fukui functions, were used to correlate and predict the electrophilic reactivity of amine groups with COS. Substituents influence the reaction rate by changing the attraction interaction of amine groups to COS molecules and the electron rearrangement in the electrophilic reaction. Furthermore, they have more pronounced steric effects on the reaction rate in the linear amines. The descriptors N_ALIE and q(N) were found to be crucial in predicting the reactivity of amine groups with COS. Present study provides a comprehensive understanding of the reaction mechanisms of COS with amine compounds, offers specific chemical principles for the development of chemistry-driven ML models, sheds light on other types of electrophilic reactions occurring on amine and phosphine groups, and guides the development of chemical solvents in gas absorption processes.

Impact of transportation infrastructure and urbanization on environmental pollution: evidence from novel wavelet quantile correlation approach

In terms of achieving sustainable development goals (SDGs), the developing economies are facing many issues, and one of the key issues is environmental degradation. Being a developing economy, Pakistan is also experiencing thought-provoking impacts of global warming and still far away from the ideal track of sustainable development. For addressing environment-related issue and achieving the targets of SDGs, a policy-level reorientation might be necessary. In this view, this study investigates the impact of economic growth, transport infrastructure, urbanization, financial development, and renewable energy consumption on CO2 emissions by using the data of Pakistan during 1990-2020. For this purpose, we use novel wavelet quantile correlation approach. The empirical results of wavelet quantile correlation approach demonstrate that economic growth, transport infrastructure, urbanization, and financial development are responsible for environmental pollution. Whereas, result also claims that renewable energy consumption is a useful tool for reducing environmental pollution in Pakistan. Moreover, the results of FMOLS approach show that 1% increase in economic growth, transportation infrastructure, urbanization, and financial development increases CO2 emissions by 0.240, 0.010, 0.478, and 0.102%, respectively. However, 1% increase in renewable energy usage reduces CO2 emission by 1.083%. Based on the empirical outcomes, this study proposes comprehensive policy framework for achieving the targets of SDG 7 (clean energy), SDG 8 (economic growth), SDG 11 (sustainable cities and communities), and SDG 13 (climate action).

Is gender diversity is diversity washing or good governance for firm sustainable development goal performance: A scoping review

In Industry 4.0, sustainability is the heart, and governance is the soul of the business, but diversity washing, greenwashing, and SDG washing are skeptical. This is due to the reactive/normative approach in dealing with sustainability and governance, which has created an amounting number of greenhouse gases, waste generation, and several business washing challenges. This study has explored the Scopus and Web of Science databases and searched for the keywords "Sustainable Development Goals" AND "Director," which provided 76 documents. However, when the authors added the third keyword, "ISO 37001-2021," along with the above two keywords, the database provided no study investigating the moderation role of ISO 37001-2021. Therefore, the study advocates the adoption of newly developed ISO 37000:2021 good governance standards for greenwashing, SDG washing, and diversity washing challenges without failing to contribute to the firm sustainable development goal performance and earning management. Secondly, the independent director attribute's role is vital due to the potential, power, position, and evidence to adopt ISO 37000:2021 standards. Thirdly, the scoping review study has proposed a conceptual model to extend the reporting discloser and transparency. It goes beyond mere compliance, contributes towards societal development, and promotes adopting sustainable development goal performance and reporting as a new non-financial parameter for evaluating the firm's performance. Lastly, this will boost firm sustainability and adopt the circular economic model, creating a unique competitive edge and green governance goodwill among the business's external stakeholders and attracting sustainably responsible investors.

Impact of renewable energy investments in curbing sectoral CO2 emissions: evidence from China by nonlinear quantile approaches

The study analyzes the impact of renewable energy investments (RENIV) on the environment in China. In doing so, the study uses sectoral carbon dioxide (CO2) emissions as the environment indicator, considers RENIV as the explanatory variable, includes monthly data from 2004/1 to 2020/6, runs quantile on quantile regression approach as the fundamental model, and further performs quantile regression for the controlling. The study reveals that RENIV curb CO2 emissions in all sectors at higher levels of sectoral CO2 emissions. Also, RENIV have a varying impact based on quantiles and sectors. Moreover, the results are robust based on the alternative approach. Thus, RENIV have a significantly decreasing impact on sectoral CO2 emissions in China. Accordingly, China policymakers should continue to focus on providing a decrease in energy and industrial sector CO2 emissions as the highest emitting sectors.

The relationship between energy and non-energy factors and CO2 emissions in New Zealand

The use of renewable energy as a fuel source and expansion of forest areas are the best ways for reducing CO2 emissions. This study aims to examine the effects of forest plantation area, renewable energies, real gross domestic product (GDP), and technological innovation on CO2 emissions in 9 regions of New Zealand between 2006 and 2019. For this purpose, it employs a pooled mean group methodology. Investigating the regional impacts of various variables, especially the forest area, on CO2 emissions is the main contribution of this study. The results suggest that planted forest areas can reduce CO2 emissions in the long run, but its impact in the short run is not significant. Non-renewable energy consumption is the major contributor to CO2 emissions in both the short and long run. While technological innovation and renewable energy consumption appear effective in reducing carbon emissions in the short term, they still contribute to increased CO2 emissions in the long term. At the regional level, we found that the forest plantation areas in Manawatu-Whanganui and Gisborne are important regions for reducing CO2 emissions. By taking account of these results, New Zealand should take swift action to properly manage and increase the current level of forest areas and if applicable expand them. It also needs to improve the current level of use of renewable energy to achieve its abatement goals.

Examining the trade-offs in clean energy provision: Focusing on the relationship between technology transfer, renewable energy, industrial growth, and carbon footprint reduction

Sustainable energy mitigates climate change by reducing reliance on coal and oil for power generation, curbing global warming. It addresses environmental concerns and yields economic benefits-reduced fossil fuel dependence, financial inclusion, productive employment, and economic development. This research examines the impact of regional economic integration on environmental sustainability in 39 high-income European and Central Asian (ECA) nations from 2017 to 2021. Specifically, the study analyzes the influence of green energy demand, technological transfers, and trade openness on carbon emissions. The study employed various estimators, namely, a two-step Generalized Method of Moments (GMM) estimation, quantile regression, and the cointegration panel approach. These estimators were utilized to capture different aspects and dynamics of the research variables. The study finds that regional green programs and trade agreements effectively reduce carbon emissions, while technological advances and industrial output tend to raise them. Granger causality analyses reveal that emissions-led regional development, technical innovation, and trade openness are interconnected factors, and the deployment of renewable energy contributes to carbon emissions. The inter-temporal analysis suggests that regional economic integration factors will likely impact carbon emissions in the following decade. These findings support neoclassical growth theory, new institutional economics, and ecological modernization theory. Developing renewable energy sources in the region can minimize energy price fluctuations, strengthen energy security, and align with the carbon neutrality agenda. This research emphasizes the need for sustainable energy strategies and regional cooperation to foster a greener and more sustainable future.

From growth to sustainability: investigating N-shaped EKC and the role of energy productivity, technological advancement, and human capital in OECD economies

Environmental degradation rates have been on a concerning upward trajectory in recent decades, directly threatening the well-being of global populations. Responding to this urgent matter, scholars have been driven to explore its nuances, particularly emphasizing lowering energy consumption and carbon emissions amidst the growing demands of growing economies. Achieving the targets outlined in the 2015 Paris Climate Agreement has also become a priority for many countries. Therefore, this study scrutinizes the Environmental Kuznets Curve (EKC) hypothesis, specifically focusing on the role of energy productivity, technological advancement, and human capital in fostering a sustainable environment across 35 OECD economies from 1990 to 2018. Utilizing three robust econometric techniques, Cross-Sectional Autoregressive Distributed Lag (CS-ARDL), Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS), we have drawn insightful conclusions from our data. The analysis substantiates an N-shaped EKC hypothesis relationship between GDP and CO2 emissions, pointing towards an initially increasing, then decreasing, and finally an increasing again trend of emissions with GDP. Furthermore, the long-term projections underscore that energy productivity, technological progression, and human capital formation harm the environment. These findings culminate in a call for governments to orchestrate extensive plans and initiatives. This involves promoting green technologies, renewable energy-based ideas, and comprehensive education and awareness programs. These efforts should span all educational levels, highlighting climate change, sustainable practices, and the need for CO2 reduction, empowering societies to contribute to a sustainable future.

The impacts of renewable energy and institutional quality in environmental sustainability in the context of the sustainable development goals: A novel approach with the inverted load capacity factor

It is crucial to fulfill sustainable development goals in combating environmental pollution. Recently, there has been a growing literature on environmental pollution; however, while many proxies represent environmental pollution, few proxies represent environmental sustainability. In this paper, we examine the effects of institutional quality (SDG-16), economic growth (SDG-8), and renewable energy (SDG-7) on the inverted load capacity factor (SDG-13) in OECD countries from 1999 to 2018. The objective is to ensure environmental sustainability within the Sustainable Development Goals (SDGs) framework. In this respect, the study differs from the existing literature by approaching the sustainable environment literature from a broader perspective. Long-term empirical estimates from the PMG-ARDL technique have shown that institutional quality, reel income, and population increase the inverted load capacity factor, that is, decrease environmental sustainability. However, on the contrary, renewable energy decreases the inverted load capacity factor. Therefore, renewable energy consumption helps reach SDG-7 and SDG-13 in OECD countries. In addition, it is found that economic growth is significant both in the long run and in the short run, and the impact of economic growth on the environment is greater in the short run than in the long run. This result supports the environmental Kuznets curve (EKC) hypothesis for OECD countries. The panel causality test results find a bidirectional causality relationship from renewable energy and population to inverted load capacity factor and a unidirectional causality relationship from institutional quality to inverted load capacity factor. This study argues that policymakers should concentrate on deploying environmentally friendly technology to slow down environmental degradation, increase the usage of renewable energy sources, and promote sustainable development in line with the SDGs.

Challenges towards the Sustainability and Enhancement of the Indian Sundarban Mangrove's Blue Carbon Stock

The Sundarban is the world's largest contiguous mangrove forest and stores around 26.62 Tg of blue carbon. The present study reviewed the factors causing a decline in its blue carbon content and poses a challenge in enhancing the carbon stock of this region. This review emphasized that recurrent tropical cyclones, soil erosion, freshwater scarcity, reduced sediment load into the delta, nutrient deficiency, salt-stress-induced changes in species composition, mangrove clearing, and anthropogenic pollution are the fundamental drivers which can potentially reduce the total blue carbon stock of this region. The southern end of the Ganges-Brahmaputra-Meghna Delta that shelters this forest has stopped its natural progradation due to inadequate sediment flow from the upper reaches. Growing population pressure from the north of the Sundarban Biosphere Reserve and severe erosion in the southern end accentuated by regional sea-level rise has left minimal options to enhance the blue carbon stock by extending the forest premises. This study collated the scholarly observations of the past decades from this region, indicating a carbon sequestration potential deterioration. By collecting the existing knowledge base, this review indicated the aspects that require immediate attention to stop this ecosystem's draining of the valuable carbon sequestered and, at the same time, enhance the carbon stock, if possible. This review provided some key recommendations that can help sustain the blue carbon stock of the Indian Sundarban. This review stressed that characterizing the spatial variability of blue carbon with more sampling points, catering to the damaged trees after tropical cyclones, estuarine rejuvenation in the upper reaches, maintaining species diversity through afforestation programs, arresting coastal erosion through increasing sediment flow, and combating marine pollution have become urgent needs of the hour. The observations synthesized in this study can be helpful for academics, policy managers, and decision makers willing to uphold the sustainability of the blue carbon stock of this crucial ecosystem.

A dynamic relationship between renewable energy, agriculture, globalization, and ecological footprint of the five most populous countries in Asia

This study aims to examine the impact of globalization, renewable energy consumption, and agricultural value addition on the ecological footprint of selected five most populous countries in Asia during the period 1975-2020. The Westerlund cointegration test supports long-term cointegration relationships among the considered variables in selected countries. The long-term resilience results of the second-generation cross-sectionally augmented autoregressive distributed lag approach evidently demonstrate that agricultural value addition and globalization contribute significantly to the long-term ecological footprint of the five most populous countries in Asia. However, renewable energy consumption significantly reduces the ecological footprint. Moreover, the impact of economic growth on ecological footprint is significantly positive, while the square of economic growth had a significantly negative impact on ecological footprint, thus validating the inverted U-shaped environmental Kuznets curve hypothesis for specific Asian densely populated countries. The causality test results of Dumitrescu and Hurlin support the feedback hypothesis by showing a two-way causal relationship between renewable energy consumption and economic growth. There is also a two-way causal relationship between agricultural value added and ecological footprint. Strategically, specific densely populated countries in Asia should encourage clean energy production and consumption in the agricultural sector, and the adoption of environmentally friendly technologies can improve environmental quality and agricultural production.

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.

Renewable energy, economic freedom and economic policy uncertainty: New evidence from a dynamic panel threshold analysis for the G-7 and BRIC countries

This study aims to demonstrate the impact of renewable energy consumption (REC) on environmental degradation using the EKC hypothesis testing for the BRIC and G-7 countries. Two EKC models were created and tested, with Model 2 including REC and other independent variables such as economic freedom (EF) and economic policy uncertainty (EPU), which affect the level of renewable energy consumption and CO2 emissions. Empirical findings indicate that the EKC hypothesis is verified faster in the REC-EF-EPU-based EKC model (Model 2) than in the EF-EPU-based EKC model (Model 1) for G-7 countries since the turning point takes place earlier in Model 2 than in Model 1 with REC. This suggests that renewable energy consumption accelerates the reduction of CO2 emissions. Moreover, this earlier turning point results in lower environmental cleaning costs, less time vesting, and saving resources and money for G-7 countries. However, the study found no evidence supporting the EKC hypothesis for the BRIC countries.

Environmental impact of globalization: The case of central and Eastern European emerging economies

Against the backdrop of piling environmental concerns in the modern era of globalization, this study aims to check the validity of the Pollution Haven Hypothesis (PHH) in Eastern European emerging countries and the relevance of globalization. The study targets to reduce the lack of consensus on the globalization-economic complexity-environment in European countries. Besides, we also intend to explore the existence of an N-shaped economic complexity-related Environmental Kuznets Curve (EKC) controlling for the bearing of renewable energy on environmental degradation. For analytical purposes, both parametric and non-parametric quantile regression approaches are employed. Overall, we find a non-linear relationship between economic complexity and carbon emissions, and N-shaped EKC is verified. Globalization and renewable energy consumption boost and inhibit emissions, respectively. More importantly, the results confirm the moderating role of economic complexity in neutralizing the carbon emissions-boosting effect of globalization. On the other hand, the non-parametric findings show that the N-shaped EKC hypothesis does not hold for high emissions quantiles. Furthermore, for all emissions quantiles, it is found that globalization boosts emissions, economic complexity, and globalization jointly curbs emissions and renewable energy curbs emissions. Based on the overall findings, some vital environmental development policies are recommended. The conclusions support shaping policy options promoting economic complexity and renewable energy as key factors in mitigating carbon emissions.

Empirics on linking industrial agglomeration, energy consumption, residential construction sector growth, and environmental sustainability

We looked at the long-term and short-term diversified relationships between industrial agglomeration, aggregate energy consumption, residential construction sector growth, and air pollution in China's 30 provincial units from 2004 through 2020. We contributed to the existing knowledge by calculating a holistic air pollution index (API) and applying advanced methods. We also augmented the Kaya identity by including industrial agglomeration and residential construction sector growth in the baseline framework. Based on empirical results: First, we revealed long-term stability among our covariates through panel cointegration analysis. Second, we uncovered a positive bilateral relationship between residential construction sector growth and industrial agglomeration in the long and short term. Third, we unfolded a unilateral positive correlation emerging from aggregate energy consumption to API, displaying the greatest influence in the east zone of China. Fourth, we observed a unilateral positive connection stemming from industrial agglomeration and residential construction sector growth to aggregate energy consumption and API in the long- and short-term dimensions. Finally, the linking nature was homogeneously prevailing across the long term and short term; however, the long-term impact size outweighed that of the short term. Given our empirical results, useful policy insights are discussed to provide the readers with a take-home message for substantiating sustainable development goals.

Determinants of environmental quality in India: evidence using the bootstrapped ARDL model with structural breaks

This current study examines the impact of renewable energy consumption, agriculture, and globalization on carbon emissions in India over the period from 1980 to 2018. For long-run estimates, we apply Gregory-Hansen's co-integration test, bootstrap ARDL approaches, fully modified ordinary least squares, and dynamic OLS. The empirical results of long-run estimates indicate that a 1% increase in renewable energy consumption, agriculture, and economic globalization will increase carbon emissions by 0.764%, 1.675%, and 0.517%, respectively. Moreover, this study confirms the detrimental effect of these variables on carbon dioxide emissions. Economic globalization coefficients indicate that the scale effect is valid in India. The 2002 economic crisis slowed down the country's growth rate, which reduced the ecological pollution. Several policy recommendations are derived from the empirical findings.

Effect of environmental taxes on environmental innovation and carbon intensity in China: an empirical investigation

Environmental taxes are deemed to be an important carbon mitigating factor and also encourage the producers to adopt environmentally friendly technologies. Therefore, the main objective of the analysis is to evaluate the environmental taxes on environmental innovations and carbon intensity in China. The novel quantile autoregressive distributed lag (QARDL) is applied to investigate the model empirically. From the results, we confer that the short and long run estimated coefficients of environmental taxes are positive and significant at most quantiles in the environmental innovation model, implying that the higher the rate of environmental taxes, the higher the rate of environment-related innovations. However, the estimates of environmental taxes are significant and negative in both short and long run at more than half quantiles in the carbon emissions model, suggesting the positive role of environmental taxes in reducing carbon emissions. In general, our findings imply that an increase in environment-related taxes helps reduce carbon intensity and promote environmental innovation in China. The study suggests that policymakers in China should promote environmental innovation and expand the environmental tax base to achieve the objective of carbon neutrality.

Role of nuclear energy in carbon mitigation to achieve United Nations net zero carbon emission: evidence from Fourier bootstrap Toda-Yamamoto

In this communication, the time series data of three major countries USA, France, and Japan from 1965 to 2020 for CO₂ emission, GDP, and nuclear energy (NE) are evaluated. It also analyzed and validated the EKC hypothesis while using nuclear energy for electricity generation. Fourier ARDL is used to investigate the hypothesis criteria, and the Fourier bootstrap Toda-Yamamoto (FBTY) causality test is used for causal linkage between the variables as well as the wavelet coherence; it is also presented the time and frequency dependency of the variables. The CO₂ mitigation by using the NE is also assessed for all three countries and assessed that the France, Japan, and USA mitigated the CO₂ per year is 0.0463 million metric ton (MMT), 0.0239 and 0.0728 MMT per year respectively. Similar to that the SO₂ is reduced by using the NE is 24.322, 43.527, and 132.592 MMT/year, and NOx is reduced by approximately 0.2847, 0.147, and 0.4478 MMT/year by France, Japan, and USA respectively by applying the NE for power generation. The evidence of the EKC, Fourier bootstrap and Toda-Yamamoto clarifies the important role of nuclear energy in terms of carbon mitigation to achieve UN net zero carbon emission by 2050. Hence, in order to meet the UN target of net zero carbon emission by 2050, the USA and Japan should increase the production of nuclear energy as France meets its 74.1% energy demand through NE by validating the EKC hypothesis; on the other hand, all the three countries should increase the production of tidal energy due to their geographical location as tides are much more predictable than wind and sun keeping in consideration to the expenses incurred and a full proof plan for disposing NE residuals in a safe place as NE residuals are highly radioactive and contains traces of thorium and uranium.

Ensuring environmental inclusion in developing countries: the role of macroeconomic policies

In every society, there exist disadvantaged groups who have failed constantly to take part in the development of the economy and reap the benefits of economic growth as well. Along with economic and social factors, environmental factors are also accountable in making inclusion a challenge for the marginalized group. Contaminated drinking water, inappropriate sanitation systems, and pollution are the factors that affect health and wellbeing of the poor class by affecting their productivity. Thus, the lack of a clean environment leads the poor section towards further poverty and income inequality. Since the 2030 Agenda for Sustainable Development emphasizes three components to achieve sustainable development, namely economic, social, and environmental, this study inspects the role of macroeconomic policies in ensuring an inclusive clean environment in developing countries. Moreover, it considers the composite effect of fiscal policy and monetary policy on environmental inclusion by including interactive terms. This investigation uses FE-2SLS on a panel of 51 developing countries for the period of 1995-2019 to analyse the impact of macroeconomic policies on environmental inclusion. The study provides empirical evidence that fiscal and monetary policy has the potential to ensure an inclusive clean environment in developing countries. The findings imply that the macroeconomic policy actions depend on each other. Furthermore, governments in developing regions are required to cut nondeveloping expenditures and use expansionary monetary policy to promote green growth.

Revisiting the impact of renewable energy consumption on economic growth: sectoral evidence from the USA

The aim of this study is to investigate the relationship between sectoral renewable energy consumption and economic growth in the US economy for the period 1950-2020 by using the Fourier component augmented unit root, cointegration, and causality analyses for the transportation, industrial, residential, electric power, and commercial sectors. Our results reveal in the long run that renewable energy will Granger cause growth through the new jobs it will create, the restructuring of the economy which is a prerequisite for replacing fossil energy with renewable energy. On the other hand, causal relationships are less stable and methodology and sector specific in the short run. Accordingly, the electric power and industrial sectors experience conservation patterns in terms of renewable energy consumption, while the growth hypothesis is confirmed for the commercial sector. Different implications are generated for each sector, which are now more important than ever given the current energy crisis in Europe and the urgent need to reduce dependence on fossil fuels.

Does globalization and energy usage influence carbon emissions in South Asia? An empirical revisit of the debate

The 2030 United Nations Sustainable Development Goal (SDG) 13 agenda hinges on attaining a sustainable environment with the need to "take urgent action to combat climate change and its impacts". Hence, this study empirically revisits the debate on the effect of nonrenewable energy and globalization on carbon emissions within the framework of the Kuznets hypothesis using an unbalanced panel data from seven South Asian countries (Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka) covering 1980-2019. The variables of interest are carbon emissions measured in metric tons per capita, energy use measured as kg of oil equivalent per capita, and globalization index. To address five main objectives, we deploy four techniques: panel-corrected standard errors (PCSE), feasible generalized least squares (FGLS), quantile regression (QR), and fully modified ordinary least squares (FMOLS). For the most part, the findings reveal that the (1) inverted U-shaped energy-Kuznets curve holds; (2) U-shaped globalization-Kuznets curve is evident; (3) inverted U-shaped turning points for nonrenewable energy are 496.03 and 640.84, while for globalization are 38.83 and 39.04, respectively; (4) globalization-emission relationship indicates a U-shaped relationship at the median and 75th quantile; and (5) inverted U-shaped energy-Kuznets holds in Pakistan but a U-shaped nexus prevails in Nepal and Sri Lanka; inverted U-shaped globalization-Kuznets holds in Bangladesh and Sri Lanka, but U-shaped nexus is evident in Bhutan, Maldives, and Nepal. Deductively, our results show that South Asia countries (at early stage of development) are faced with the hazardous substance that deteriorates human health. Moreover, the non-linear square term of the nonrenewable energy-emissions relationship is negative, which validates the inverted U-shaped EKC theory. Overall, the effect of energy and globalization on carbon emissions is opposite while the consistency at the 75th quantile result indicates that countries with intense globalization are prone to environmental degradation.

Are economic growth and environmental pollution a dilemma?

For the first time, this study introduces-proposes using the Armey curve hypothesis (ACH) for testing the environmental Kuznets curve hypothesis (EKCH) in the relevant literature. The rationale for this new proposed methodology is that both hypotheses are expected to have similar inverted U-shaped curves. Hence, we combine the aforementioned hypotheses to obtain a single composite model. This single model may allow us to calculate a maximum (optimum) level of government expenditures that will increase or decrease CO₂ emissions for USMCA (the USA-Mexico-Canada Agreement) countries. To this end, our study employs an augmented mean group (AMG) estimator. The results demonstrate that the EKCH is verified by way of the AC model only for Mexico. Additionally, with the advantage of this approach, we calculated the optimal government spending level, which will increase both per capita real GDP (RGDPPC) and CO₂ emissions in this country by around 26.4% of RGDPPC. This level of spending will be a kind of threshold point for the Mexican government's policymakers. Hence, they will know that if they continue to spend more than this level, both the RGDPPC and CO₂ emissions will decrease, implying either a lower RGDPPC or a cleaner environment. The primary purpose of the proposed methodology in this study is to reveal the possible effects of the government's economic growth-oriented increased public expenditures on the environment in a single composite model. In other words, the relationship between economic growth and the environment is approached from the perspective of public spending, and it is reminded that governments should have harmonious and sustainable public spending policies for both economic growth and a cleaner environment.

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.

Drivers of green growth in the Kingdom of Saudi Arabia: can financial development promote environmentally sustainable economic growth?

The Kingdom of Saudi Arabia has recently declared its vision of turning carbon neutral by 2060. This declaration has motivated policymakers in this Arab nation to design policies that can green economic activities in Saudi Arabia so that environmentally sustainable growth can be ensured. Against this backdrop, this study models the independent and joint effects of financial development, globalization, and energy efficiency rates on green growth of the Saudi Arabian economy. In this regard, green growth in the Kingdom of Saudi Arabia is proxied by the difference between the nation's annual per capita growth rates of gross domestic product and carbon dioxide emission. Utilizing data from 1972 to 2018 and controlling for structural break-induced problems found in the data, the findings from the regression and causality analyses confirm the green growth-inhibiting impacts of financial development and trade globalization. In contrast, greater financial globalization is evidenced to drive green growth in the Kingdom of Saudi Arabia. Furthermore, more efficient uses of energy resources are found to not only directly boost green growth but also partially neutralize the long-run green growth-dampening impacts associated with the development of the financial sector. In addition, financial development and trade globalization are observed to jointly inhibit green growth attainment both in the short and long run. In line with these important findings, it is recommended that the government of Saudi Arabia conceptualizes new green growth policies so that the nation's annual per capita economic growth rate outpaces its annual per capita growth rate of carbon dioxide emissions.

Exploring the dynamic nexus between renewable energy, poverty alleviation, and environmental pollution: fresh evidence from E-9 countries

The present study aims to scrutinize the long- and short-run relationship along with the direction of causality among environmental pollution (CO₂), renewable, non-renewable energy, income disparity, exchange rate, and poverty alleviation in E-9 countries of continent Asia, using a panel dataset from 1990 to 2018. The current study used pooled mean group autoregressive distributed lag (PMG ARDL) and Dumitrescu-Hurlin (D-H) causality test after affirming a stable long-run association among environmental pollution and all the explanatory variables. However, ECM (error correction mechanism) was specified to explore short-run dynamics. The study's outcomes confirmed strong co-integration among environmental pollution (CO₂), renewable, non-renewable energy, income disparity, exchange rate, and poverty alleviation. Moreover, uni (bi) directional causality runs from non-renewable energy, exchange rate, and income disparity (poverty alleviation and renewable energy) to environmental pollution (CO₂). Results also revealed that poverty alleviation, exchange rate, and renewable energy usage substantially negatively influence environmental pollution (CO₂). Contrarily, income disparities and non-renewable energy usage positively influence long- and short-run environmental pollution. Therefore, from the policy perspective, the current study focused on twofold; first, there is a desire to alleviate poverty, the decline in non-renewable energy use and income disparity among upper and lower-income quintiles. Second, boost exchange rate and renewable energy use to control environmental pollution in the described least developed countries (LDCs).