Can CO2 emissions and energy consumption determine the economic performance of South Korea? A time series analysis

Harnessing technological innovation and renewable energy and their impact on environmental pollution in G-20 countries

Climate change and environmental degradation are critical global challenges, and the G-20 nations play a pivotal role in addressing these issues due to their substantial contributions to global GDP and carbon emissions. Transitioning toward renewable energy sources is imperative for mitigating CO2 emissions and achieving sustainable development. This study investigates the impact of technological innovation, gross domestic product (GDP), renewable energy consumption, economic freedom, and financial advancement on renewable energy use and environmental pollution levels in G-20 countries from 1995 to 2022. Utilizing the PMG-ARDL dynamic panel method, the research analyzes both long-term and short-term relationships among the variables. The findings reveal that technological innovation significantly boosts renewable energy adoption, with a 1% increase in technological innovation leading to a 0.33% rise in renewable energy use in the long run and a 0.17% increase in the short run. Additionally, increased renewable energy consumption is strongly associated with reductions in CO2 emissions, highlighting its critical role in promoting environmental sustainability. The study emphasizes the importance of policies designed to enhance technological innovation to foster renewable energy usage and reduce environmental pollution. It recommends expanding and reforming the technological sector to align international and local resources with renewable energy initiatives, providing a workable framework for supporting the green growth of institutions and achieving a more sustainable future for G-20 nations. This research contributes to understanding the intricate dynamics of renewable energy transitions, offering actionable insights for policymakers and stakeholders in addressing global environmental challenges.

The impact of renewable and non-renewable energy consumption on aggregate output in Pakistan: robust evidence from the RALS cointegration test

Over the past three decades, Pakistan's energy consumption has surged due to industrialization, population growth, and development activities. To meet the escalating energy demands, the country has primarily relied on thermal power projects, which are financially burdensome and environmentally detrimental, compared to hydropower projects. This reliance exposes Pakistan to global oil price shocks and environmental degradation. To address this dilemma, this empirical research investigates the impact of both non-energy factors (labour and capital) and energy-specific factors (renewable and non-renewable) on Pakistan's aggregate output, using annual time-series data from 1980 to 2021. The analysis employs the newly established Residual Augmented Least Square (RALS) cointegration test and the Autoregressive Distributed Lag (ARDL) methodology to estimate the long-term cointegrating relationship among the examined variables. The empirical findings demonstrate that both non-energy and energy-specific factors positively and significantly influence Pakistan's long-term aggregate output. However, petroleum consumption exerts a positive but insignificant influence on Pakistan's long-term aggregate output. The study recommends diversifying the energy supply mix to include more hydroelectricity, non-hydroelectric renewables (mainly solar and wind), and natural gas. Specifically, transitioning from imported, expensive, and more greenhouse gas (GHG)-generating petroleum products to domestically produced natural gas could potentially reduce Pakistan's trade deficit and its vulnerability to global oil price shocks. Besides the economic benefits, shifting from non-renewable energy sources (specifically oil) to renewable energy would enhance Pakistan's image and increase its geopolitical influence over neighboring countries. Additionally, the study emphasizes the need to encourage private sector participation in renewable energy projects and suggests implementing effective carbon tax policies to mitigate CO2 emissions and foster economic growth.

Assessment of the heterogeneous impacts of global value chain participation on Sustainable economic growth and environmental quality

The Global Value Chain (GVC) is an essential aspect of sustainable economic growth and environmental quality in countries that participate in it. Therefore, comprehending the relationship between GVC and economic growth and carbon emissions is critical to achieving global climate neutrality targets. However, there is a paucity of knowledge regarding the impacts of disaggregated levels of GVC on economic growth and carbon emissions in countries with different income levels. In this study, we utilized the SYS-GMM model to explore the relationships between backward and forward GVCs and the economic growth and carbon emissions of 42 lower-middle, 36 middle-upper, and 48 high-income countries using data from 1995 to 2018. Our key findings suggest that forward GVC significantly increases economic growth and reduces CO2 emissions. Conversely, backward GVC reduces the economic growth and CO2 emissions of high-income countries. We also found that upper-middle-income economies can enhance their economic growth and reduce CO2 emissions by increasing their backward GVC. In contrast, lower-middle-income economies can increase their economic growth by participating in both forward and backward GVCs. However, higher levels of participation in both GVC components result in increased CO2 emissions. Our findings emphasize the importance of considering income levels when analysing the impact of GVC participation on economic growth and environmental sustainability. Overall, the relationship between economic growth and CO2 emissions with backward and forward GVCs varies significantly across country categories.

Spatial-structural analysis of macroeconomic factors' impact on carbon emissions in East Africa: a spatial econometric panel study

Despite the abundance of research on reducing carbon emissions, there is a significant gap in understanding the influence of macroeconomic factors on carbon dioxide (CO2) emissions from a spatial-structural perspective. This study aims to contribute to the literature by investigating the impact of macroeconomic factors on carbon dioxide emissions in six East African countries between 1989 and 2020. Using spatial econometric panel models, the study analyzed spatial dependence among the variables. The empirical findings indicate that gross domestic product (GDP) per capita and electricity consumption have positive direct and indirect effects on carbon emissions, while fuel prices and exports have negative direct effects, but positive spillover effects on neighboring countries. Imports have a positive impact on local economies, but negative spillover effects. Additionally, the urban population has no significant impact on the environment. These findings provide important policy implications for optimizing spatial growth patterns and achieving a low-carbon economy in East African countries.

Review of measurement of sustainable development goals: a comprehensive bibliometric and visualized analysis

The global focus on evaluating environmental performance means that sustainable development goals must be prioritized to preserve environmental sustainability. In order to accomplish the SDGs, it is crucial that activities be preferred and that methods be developed to assess their effectiveness. As a result, the techniques used for the measurement and assessment of the SDGs have increased in significance for all countries. Researchers and academics create these technologies through research and invention. By undertaking a bibliometric analysis, this study aims to identify the scholarship in the area of SDG assessment and measurement. The analysis was produced by collecting the related studies from the Web of Science database. The information was retrieved, and a thorough and organized analysis was done to give crucial insights on the chosen issue. The analysis revealed the most often cited articles, important institutions that contributed, leading research-involved nations, and institutions. To evaluate the varied collection of techniques accessible for the goal of evaluating SDGs, a thorough review of the most cited works is conducted and provides a bird's eye view of research on mechanisms for measuring the outcomes of SDGs.

Green finance, energy consumption, urbanization, and economic growth: Quantile based evidence from China

This study investigates the relationships between energy consumption, urbanization, green finance, and economic growth in China. By utilizing the quantile ARDL model and considering labor and capital as input factors, we analyze the period from 1999 to 2022. Our findings reveal that green finance and urbanization have negative effects on economic growth across different quantiles, in both the short and long run. Conversely, energy consumption exhibits a significantly positive impact on growth in various quantiles. Policymakers are encouraged to implement sustainable energy measures, promote eco-friendly urban planning, and embrace green technology to achieve both economic growth and environmental sustainability.

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.

Climate change, the by-product of tourism and energy consumption through a sustainable economic growth: a non-linear ARDL analysis for Turkey

Using a non-linear autoregressive distributed lag time-series analysis, this paper investigates the causal relationship between climate change, the tourism sector, and energy consumption in Turkey. The trade-off between a country's economic growth and the environmental degradation caused by tourism and the energy sector is critical in terms of scientifically addressing the issue and developing economic policies. As a result, climate change is used as the dependent variable and is represented by precipitation and temperature separately; the independent variables are tourist arrivals, energy consumption, and economic growth. Data is gathered by various institutions from 1995 to 2020. According to the test results, while positive and negative shocks contribute to the decrease in precipitation and temperature in renewable energy consumption (REC) in the long-run, they affect the increase in precipitation and temperature in non-renewable energy consumption (NREC). In the long-run relationship between tourism and temperature, a decrease in the number of tourist arrivals causes a decrease in temperature and precipitation. The findings reveal that a decrease in the number of tourist arrivals and an increase in REC may aid in decreasing temperature, while the increase in NREC may cause an increase in temperature. Through a case study of Turkey, decision-makers should consider these scientific findings that are in the frame of non-linear analysis as possible scenarios for mitigating climate change and fostering sustainable economic growth with efficient tourism policies for the world.

Trilemma of capital, urbanization, and renewable energy: contextual evidence from China

In the case of China, there is a need of green energy system to boost growth and environment. However, the current growth of urbanization is putting high pressure on energy system through financial capital. Hence, it is a need to develop such path through renewable energy consumption, capital development, and urbanization to enhance the performance of development and environment. Therefore, this paper contributes to the literature by adding the asymmetries between renewable energy, urbanization, economic growth, and capital investment by covering the period from 1970 to 2021. For this purpose, we apply the nonlinear autoregressive distributed lag model to find the nonlinearities between the variables under study. The findings confirm the asymmetric short- and long-term relationships between the variables. In this sense, capitalization shows the short- and long-term asymmetric impacts on renewable energy consumption. In addition, urbanization and economic growth have long-term asymmetric and positive impacts on renewable energy consumption. At last, this paper provides applicable and practical policy implications for China.

Asymmetrical effects of renewable energy consumption, financial development, and urbanization on the economic growth of China: does the role of technology matters

Our paper investigates the association of renewable energy, financial development, urbanization, and growth in China along with technology. The newly developed econometric techniques (asymmetries) have been applied to explore short and long-run nonlinear relation among variables by utilizing annual data for the period of 1965-2021. In nonlinear cointegration, findings highlight the importance of renewable energy consumption for growth and development. Urbanization also confirms a positive association with growth and development where positive shocks were more dominant to support the growth process. The stock of technology brings a positive impact on growth and development whereas financial development results reveal to consider policy carefully. Asymmetric causality supports a uni-directional causal association between renewable energy, financial development, and growth. Policy recommendations are also highlighted according to the results.

Enhancing environmental quality in Portugal: can CO2 intensity of GDP and renewable energy consumption be the solution?

Despite Portugal's effort to reduce carbon emissions, the country still emits about 1.6% of the European Union's CO₂ emissions. Meanwhile, limited empirical studies have been undertaken in the context of Portugal. As a result, this study examines the asymmetric and long-term impact of CO₂ intensity of GDP, energy consumption, renewable energy and economic growth on CO₂ emissions in Portugal from 1990 to 2019. The nonlinear autoregressive distributed lag (NARDL) is employed to uncover the asymmetric connection. The findings show that there is nonlinear cointegration among the variables. The long-run estimation reveals a positive change in energy consumption positively affects CO₂ emissions, while a negative shock in energy consumption has a neutral effect on CO₂ emissions. Furthermore, positive shocks of economic growth and CO₂ intensity of GDP enhance environmental deterioration by increasing CO₂ emissions. Meanwhile, the negative shock of these regressors positively impacts CO₂ emissions. In addition, positive shocks in renewable energy enhance environmental quality, while negative shocks in renewable energy increase environmental deterioration in Portugal. Policymakers should focus on reducing per-unit energy usage and CO₂ efficiency gains, which would necessitate a significant reduction in CO₂ intensity and energy density of GDP.

Energy-growth hypothesis: testing non-linearity by considering production function approach for Spanish economy

Targeting output growth is among one of the prime concerns of any economy in both the developing and developed world. Energy utilization and exports are important drivers that would help in boosting production activities in any economy. Therefore, beyond labor force and capital formation, exports and energy utilization can be among the important inputs for accelerating economic growth in any economy. This research is conducted to investigate the linear impact of exports and the non-linear effect of energy consumption on economic growth considering the production function approach in the Spanish economy. After considering the bounds test for a period from 1980 to 2019, the study provides evidence of the inverted-U-shaped effect of energy consumption on economic growth. The findings also expose that exports, labor force and capital formation significantly accelerate economic growth in Spain. These findings are consistent with the diagnostics applied in the study. This research proposes that energy consumption should not be increased beyond a certain threshold for reaping the positive fruits of economic growth. Beyond that cutoff, it will become harmful to economic growth. Policy advisors may consider exports to target economic growth in Spain as it helps in expanding production activities in the Spanish economy.

Do natural resource volatilities and renewable energy contribute to the environment and economic performance? Empirical evidence from E7 economies

The economies of the emerging seven (E7) are not insulated from the climate change challenges, which is a key concern for most countries. The E7 nations have undertaken part in initiatives to combat climate change, particularly in terms of reducing CO₂ emissions from the trajectory of productivity expansion in their countries. It is for this reason that this study examines the impact of resource volatility, renewable energy, and fossil fuel on both economic performance and CO₂ emission from 1990 to 2018. The present study used panel quantile regression and Driscoll-Kraay fixed effect-OLS estimators to examine these associations. From model I, the outcome shows that economic performance, natural gas rent, coal rent, and fossil fuel impact CO₂ emission positively. Moreover, oil rent, renewable energy, investment in energy, and the interaction between investment in energy and renewable energy also negatively and significantly impact CO₂ emission. On the other hand, model II which has economic performance as a dependent variable shows that all the understudy variables have significant positive relations with economic performance. Based on the empirical outcome, policy ramifications are provided.

The effect of gross domestic product, urbanization, trade openness, financial development, and renewable energy on CO2 emission

The purpose of this study is to analyze the influence of GDP, urbanization, trade openness, financial development, and renewable energy consumption on CO₂ emissions in Pakistan using yearly time series data from 1985 to 2018. The study utilized the cointegration technique and Granger causality for empirical estimation. The results of the study indicated that urbanization, financial development, and trade openness upsurge CO₂ emission. Whereas using renewable energy resources is favorable for the environment and possesses negative relation with CO₂ emission. All variables possess long-run relation with Co₂ emission. Granger causality shows unidirectional causality from GDP and renewable energy to CO₂ emission. The study contains insight for policymakers in Pakistan with beneficial policy recommendations to work toward a sustainable green environment.

Energy mix with technological innovation to abate carbon emission: fresh evidence from Mexico applying wavelet tools and spectral causality

The global warming issue arises from climate change, which draws scientists' attention toward cleaner energy sources. Among clean sources, renewables and nuclear energy are getting immense attention among policymakers. However, the significance of nuclear energy in reducing CO₂ emissions has remained ambiguous, necessitating further research. Therefore, the present study draws impetuous attention to the United Nations Sustainable Development Goals-7 (affordable clean energy) & 13 (climate change mitigation) by looking at the relationship between energy mix (fossil fuels, renewables, and nuclear), economic growth, technological innovation, and CO₂ emissions in Mexico from 1980 to 2019 using the autoregressive distributed lag (ARDL) model. In addition, to assess the direction of causality, this study applied wavelet techniques and spectral causality. The findings affirm that renewable and nuclear energy use and technological innovation tend to curb CO₂ emissions, whereas fossil fuel consumption and economic expansion trigger CO₂ emissions. The study lends support to the environmental Kuznets curve (EKC) phenomenon in Mexico. The FMOLS and DOLS tests show that our long-run estimates are reliable. In different time scales, the wavelet coherence result is also consistent. Finally, the results of the spectral causality approach demonstrate a significant causal association between the variables tested at various frequencies. As a result, in order to achieve SDGs 7 and 13 and support an environmentally friendly ecosystem, Mexico's energy mix must be changed to renewables and nuclear.

Toward the Fourth Industrial Revolution among E7 Economies: Assessment of the Combined Impact of Institutional Quality, Bank Funding, and Foreign Direct Investment

Technological innovation and its paradigm, that is, the Fourth Industrial Revolution-4IR, have shown strong impact on income levels of adopters across the globe. To this end, this analysis examines the impact of bank funding and institutional quality on technological advancement. This study adds additional variables such as high-technology exports and foreign direct investment (FDI) as control variable. Our study period spans from 2000 to 2018 on an annual frequency for E7 economies (Brazil, Indonesia, Mexico, India, Turkey, Russia, and China). This study leverages on cross-sectional ARDL, Augmented Mean Group (AMG), and Common Correlated Effects Mean Group Estimates (CCEMG) estimation techniques to examine long-run relationship between the outlined variables. Empirical findings show that institution quality, bank finance, income, high-technology exports, and foreign direct investments exert a positive effect on advancements in technology. Furthermore, the interaction between bank finance and institution quality on technological advancement is also positive and statistically significant. Based on the findings, it is concluded that large-scale funding is crucial for businesses to leverage revolutionary technology. Likewise, access to large capital sources if made easier encourages technology affordance as well as innovation and operational excellence. Thus, economies with established legal and financial systems stand to offer businesses such security, which encourages business innovation. Consequently, E7 economies ought to improve their financial and legal systems to boost financial security, creativity, and competitiveness of businesses.

Investigating the moderating role of economic policy uncertainty in environmental Kuznets curve for South Africa: Evidence from the novel dynamic ARDL simulations approach

South Africa, one of the emerging markets and fast-developing economies in Sub-Saharan Africa recognised for varying world's natural assets on the international market, has recorded significant economic growth in the previous several years. However, aside from the ecological repercussions of energy generation, how economic uncertainties moderate the effects of energy intensity, renewable and non-renewable energy usage, and economic complexity on the environment has largely gone unnoticed. As a result, this paper addresses an important empirical vacuum by exploring the moderating influence of economic policy uncertainty in the environmental Kuznets curve for South Africa from 1960 to 2020. Results from the novel dynamic autoregressive distributed lag simulations framework reveal the following key findings: (i) economic policy uncertainty accelerates environmental degradation in both the short and long run; (ii) economic growth (as measured by the scale effect) increases environmental degradation, whereas the square of economic growth (as measured by the technique effect) slows it down, confirming the presence of the environmental Kuznets curve (EKC) hypothesis; (iii) environmental quality is deteriorated by energy intensity, economic complexity, non-renewable energy usage, and trade openness; (iv) the use of renewable energy and technological innovation increase environmental quality; (v) whereas the moderating effects of economic policy uncertainty on the environmental impacts of energy intensity, renewable and non-renewable energy consumption result in an increase in environmental destruction, its moderating effect on environmental implication of economic complexity plays an important role in improving environmental quality. These findings permit us to draw important policy recommendations for South Africa for improving environmental quality.

Hydrothermal carbonization improves the quality of biochar derived from livestock manure by removing inorganic matter

The application of hydrothermal carbonization to improve biomass-derived energy sources is crucial because of insufficient supplies of fossil fuels and concerns associated with the impact of fossil fuels on the environment. Hydrothermal carbonization technology has been developed to circumvent the energy-intensive drying step required for the thermal conversion of high-moisture organic feedstocks into fuel. In this study, the quality of livestock manure was upgraded, and its energy density was increased through hydrothermal carbonization at various temperatures. The evolution of waste biomass under hydrothermal carbonization was chemically analyzed. The increased carbon content of the resulting biochar upgraded its fuel properties, leading to energy savings in the treatment process. After hydrothermal carbonization, the H/C and O/C ratios were lower owing to chemical conversion. The optimal temperature for hydrothermal carbonization was approximately 220 °C. The inorganic content resulted in a lowered degree of agglomeration and reduced the likelihood of fouling during combustion. The thermogravimatric analysis also provided the changing combustion characteristics due to the increased fixed carbon content. Fourier transform infrared spectra revealed that hydrothermal carbonization reaction reduced the numbers of C-O and C-H functional groups and increased the number of aromatic C-H functional groups. The equilibrium moisture content decreased rapidly when hydrothermal carbonization was conducted at temperatures higher than 200 °C, and the initial moisture content was reduced by 75% after hydrothermal carbonization at 300 °C.

A path towards carbon mitigation amidst economic policy uncertainty in BRICS: an advanced panel analysis

Continuing economic progress with less environmental damage and achieving a sustainable environment require switching from fossil fuels to green energy. However, alleviating environmental damage of growth has become a major challenge for BRICS where economic progress amidst rising urbanization pollutes the environment. In this context, the fight against climate change and actions towards environmental sustainability are greatly affected by rising economic policy uncertainty. Hence, this study assesses the role of green energy, urbanization, and economic growth in CO2 emissions in the presence of economic policy uncertainty in BRICS (excluding South Africa) from 1997 to 2020. The study used the cross-sectionally augmented auto-regressive distributive lag technique for revealing the short- and long-run effects of the analyzed variables on environmental quality. The empirical evidence suggested that the environmental Kuznets curve exists according to the recent framework of Narayan and Narayan Energy Policy 38:661-666, (2010) because even though economic growth increases CO2 emissions, its long-run effect is less than the short-run effect. Economic policy uncertainty boosts CO2 not only in the short-run but also in the long-run, evidencing that a sustainable environment requires decreasing the levels of policy uncertainty. For BRICS, switching towards green energy is a vital option to decrease environmental deterioration owing to the negative connection between green energy and CO2. The findings indicated that rapid urbanization is among the causes of high CO2. Furthermore, economic policy uncertainty influences both green energy and economic growth levels. Finally, policies are recommended to mitigate environmental deterioration.

Exploring the asymmetric determinants of consumption and production-based CO2 emissions in China

Environmental pollution has intensified significantly in the last few decades. Policymakers have considered this issue due to its direct influence on human lives throughout the globe. This study explores the asymmetric determinants of consumption-based and production-based CO₂ emissions for China, for time horizon 1990-2019. ARDL and NARDL regression approaches have been adopted for empirical investigation. The ARDL regression method reveals that GDP does not produce any impact on production-based and consumption-based CO₂ emissions, while energy use contributes as an increasing determinant of consumption-based and production-based CO₂ emissions in the long-run. The NARDL regression method reveals that a positive shock in GDP is beneficial for a decline of consumption-based CO₂ emissions, while it does not reduce production-based CO₂ emissions in the long-run. However, negative shock in GDP contributes as an increasing determinant of consumption-based CO₂ emissions. Results also report that positive shock in energy use behaves as an increasing agent of consumption-based and production-based CO₂ emissions in the long-run, while negative shock in energy use produces a decline in production-based CO₂ emissions in the long-run. Thus, policymakers should adopt such demand and supply sides' management policies that contribute to controlling CO₂ emissions.

Impacts of globalization and energy consumption on environmental degradation: what is the way forward to achieving environmental sustainability targets in Nigeria?

One of the major problems the world is currently facing is climate change. This is due to the use of fossil fuel combustion, which increases the presence of CO₂ emissions and other greenhouse gases in the atmosphere in several countries of the world, which Nigeria is not exempted from. Against this background, this study examines the impacts of globalization, real income, urbanization, and energy consumption on environmental degradation; and proffer way forward to achieving environmental sustainability targets in Nigeria, using quarterly frequency time series data over a period 1971-2018. To achieve our study objectives, this study makes use of quantile-quantile (Q-Q) approach, developed by Sim and Zhou J Bank Financ 55:1-8, (2015). This approach groups together nonparametric estimation and quantile regression. Empirical results show that, in all quantiles, globalization, real income, urbanization, and energy consumption impact positively on environmental degradation. Thus, we are of the opinion that for the nation to achieve any meaningful environmental sustainability targets, (i) it must shift from economic activities that are dependent and driven by non-renewable energy sources; (ii) enact environmental laws and regulations that prevent indigenous and multinationals firms from using non-renewable energy sources in production activities; (iii) discourage rural-urban migration by enacting policies that would improve life in the rural areas, such as diverting investment of indigenous and multinational companies to be situated in the rural areas; and lastly, (iv) learn from jurisdictional experiences that have successfully replaces non-renewable energy sources with renewable ones for an overall economic growth and environmental sustainability targets for both the immediate and future generations.

Toward a sustainable environment and economic growth in BRICS economies: do innovation and globalization matter?

Over the last few decades, environmental deterioration has accelerated significantly. Environmental degradation has been a subject of research across the world because of its impact on billions of people. However, there has been no international agreement on lowering the utilization of energy and CO₂ emissions (CO₂), while demand for fossil fuels grows in emerging economies. On the other hand, the recent COP26 summit brought all parties together to accelerate action toward reaching the goals of the Paris Agreement and the UN Framework Convention on Climate Change. Although previous research shows that international trade promotes positive socioeconomic outcomes, other experts argue that it contributes to natural resource shortages and ecological deterioration. Thus, the current research considers the effect of international trade, renewable energy use and technological innovation on consumption-based carbon emissions (CCO₂), coupled with the role of financial development and economic growth in the BRICS economies between 1990 and 2018. Moreover, this research utilizes the common correlated effects mean group (CCEMG), augmented mean group (AMG) and Dumitrescu and Hurlin (2012) causality methods to assess these interrelationships. The study findings reveal that renewable energy use, exports and technological innovation mitigate CCO₂, whereas economic growth and imports trigger CCO₂ in the BRICS economies. The panel causality outcomes also reveal that all the variables except financial development can predict CCO₂ emissions. Based on the study findings, we recommend the adoption of policies, regulations and the development of legislative frameworks that promote technological innovation and the shift toward sustainable energy.

Does the Moderating Role of Financial Development on Energy Utilization Contributes to Environmental Sustainability in GCC Economies?

This present research examined the association among carbon emissions, financial development, economic growth, natural resources, and energy usage in GCC nations within the environmental Kuznets curve framework by applying the datasets between 1995 and 2019. It used some empirical approaches, including second-generation unit roots and cointegration methods and method of moments quantile regression (MMQR). We detected a cointegrating interconnection between carbon emissions and financial development, energy usage, economic growth, natural resources, and squared of economic growth in the long term. Furthermore, the findings of the MMQR reveal that economic growth, financial development, energy usage, and natural resources degrade the environment, as well as proving the presence of the EKC hypothesis. Moreover, the results also demonstrated that financial development greatly moderates energy usage in order to attain environmental sustainability. Furthermore, the fixed-effect ordinary least squares, fully modified ordinary least squares, and dynamic ordinary least squares were also used in the study as a soundness check of the MMQR approach. The path of causality moves from financial development, economic growth, and squared of economic growth to CO2 emissions. Lastly, the causality direction runs from carbon emissions to energy usage. Based on these findings, the energy mix of the region must be revised by ensuring the promotion of sustainable energy sources and other energy-efficient technology in order to attain the quality of the environment.

Forest Area, CO2 Emission, and COVID-19 Case-Fatality Rate: A Worldwide Ecological Study Using Spatial Regression Analysis

Spatial analysis is essential to understand the spreading of the COVID-19 pandemic. Due to numerous factors of multi-disciplines involved, the current pandemic is yet fully known. Hence, the current study aimed to expand the knowledge on the pandemic by exploring the roles of forests and CO2 emission in the COVID-19 case-fatality rate (CFR) at the global level. Data were captured on the forest coverage rate and CO2 emission per capita from 237 countries. Meanwhile, extra demographic and socioeconomic variables were also included to adjust for potential confounding. Associations between the forest coverage rate and CO2 emission per capita and the COVID-19 CFR were assessed using spatial regression analysis, and the results were further stratified by country income levels. Although no distinct association between the COVID-19 CFR and forest coverage rate or CO2 emission per capita was found worldwide, we found that a 10% increase in forest coverage rates was associated with a 2.37‰ (95%CI: 3.12, 1.62) decrease in COVID-19 CFRs in low-income countries; and a 10% increase in CO2 emission per capita was associated with a 0.94‰ (95%CI: 1.46, 0.42) decrease in COVID-19 CFRs in low-middle-income countries. Since a strong correlation was observed between the CO2 emission per capita and GDP per capita (r = 0.89), we replaced CO2 emission with GDP and obtained similar results. Our findings suggest a higher forest coverage may be a protective factor in low-income countries, which may be related to their low urbanization levels and high forest accessibilities. On the other hand, CO2 can be a surrogate of GDP, which may be a critical factor likely to decrease the COVID-19 CFR in lower-middle-income countries.

Asymmetric nexus between technological innovation and environmental degradation in Sweden: an aggregated and disaggregated analysis

The number of studies on the relationship between technological innovation and CO₂ emissions has gradually increased in recent years, although there is no clear agreement in the literature. Previous research has revealed both positive and negative consequences of technological innovation on the environment. Moreover, most researchers have used linear approaches to explore this connection, which can result in spurious outcomes when nonlinearities exist in the data. According to this background, this research utilizes asymmetric ARDL and spectral causality approaches to assess the asymmetric connection between technological innovation and CO₂ emissions in Sweden utilizing data from 1980 to 2018. In addition, the disaggregated asymmetric effects of technological innovation (patent resident and patent nonresident) on CO₂ are also captured in this study. The Nonlinear Autoregressive Distributed lag (NARDL) results showed that positive (negative) shocks in economic growth enhance environmental quality in Sweden. Furthermore, a positive (negative) shock in technological innovation causes a decrease (increase) in CO₂. Similarly, a positive (negative) shock in patent nonresident and residents leads to a decrease (increase) in CO₂ emissions in Sweden. The outcomes from the spectral causality revealed that in the medium and long term, aggregate and disaggregate technological innovation can predict CO₂ emissions in Sweden. This study has significant policy implications for policymakers and the government in Sweden. Based on these findings, the study suggests that the government of Sweden should investment in technological innovation since it plays a vital role in curbing environmental degradation.

Wavelet analysis of impact of renewable energy consumption and technological innovation on CO2 emissions: evidence from Portugal

This paper uncover a new perception of the dynamic interconnection between CO₂ emission and economic growth, renewable energy use, trade openness, and technological innovation in the Portuguese economy utilizing innovative Morlet wavelet analysis. The research applied continuous wavelet transform, wavelet correlation, the multiple and partial wavelet coherence, and frequency domain causality analyses are applied on variables of investigation using dataset between 1980 and 2019. The result of these analyses disclosed that the interconnection among the indicators progresses over time and frequency. The present analysis finds notable wavelet coherence and significant lead and lag interconnections in the frequency domain, while conflicting relationships among the variables are found in the time domain. The wavelet analysis according to economic viewpoint affirms that renewable energy consumption helps to curb CO₂ while trade openness, technological innovation, and economic growth contribute to CO₂. The outcomes also proposed that renewable energy consumption decreases CO₂ in medium and long run in Portugal. Therefore, policymakers in Portugal should stimulate investment in renewable energy sources, establish restrictive laws, and enhance energy innovation.

Towards Environmental Sustainability in China: Role of Globalization and Hydroelectricity Consumption

Countries encounter conflicting policy options in reaching fast development goals due to high resource use, rapid economic expansion, and environmental degradation. Thus, the present research examined the connection between CO2 emissions and urbanization, globalization, hydroelectricity, and economic expansion in China utilizing data spanning the period between 1985 and 2018. The novel quantile-on-quantile (QQ) and quantile regression (QR) approaches were applied to assess this interconnection. The QQ approach is characterized by its ability to incorporate quantile regression fundamentals and non-parametric estimation research. As a result, the method appears to transform the quantile of one parameter into another. The QQ outcomes revealed that in all quantiles (0.1–0.95), gross domestic product (GDP), urbanization, and globalization trigger CO2 emissions in China, while in each quantile (0.1–0.985), hydroelectricity consumption mitigates CO2 emissions. The QR outcomes also affirmed the outcomes of the QQ regression estimates. Policies are suggested based on these findings.

A new perspective into the impact of renewable and nonrenewable energy consumption on environmental degradation in Argentina: a time-frequency analysis

In most nations across the world, the fundamental goal of economic policy is to achieve sustainable economic growth. Economic development, on the other hand, may have an influence on climate change and global warming, which are major worldwide concerns and problems. Thus, this research offers a new perceptive on the influence of renewable and nonrenewable energy consumption on CO₂ emissions in Argentina utilizing data from the period between 1965 and 2019. The current research applied the wavelet tools to assess these interconnections. The outcomes of these analyses reveal that the association between the series evolves over both frequency and time. The current analysis uncovers notable wavelet coherence and significant lead and lag connections in the frequency domain, while in the time domain, contradictory correlations are indicated among the variables of interest. From an economic perspective, the outcomes of the wavelet analysis affirm that in the medium and long term, renewable energy consumption contributes to environmental sustainability. Furthermore, in the medium term, trade openness mitigates CO₂, although in the long term, no significant connection was found. Moreover, both nonrenewable energy and economic growth contribute to environmental degradation in the short and long term. Finally, the frequency domain causality outcomes reveal that in the long term, economic growth, trade openness, and nonrenewable energy can predict CO₂ emissions. The present analysis offers an innovative insight into the interconnection and comovement between CO₂ and trade openness, renewable energy utilization, and GDP in the Argentinean economy. The findings from this research should be of interest to economists, researchers, and policymakers.

Accessibility, affordability, and efficiency of clean energy: a review and research agenda

Clean, affordable, and efficient energy sources are inevitable for a sustainable world. Energy crisis, especially the poor access and affordability, demand-supply mismatches, energy inequality, and high dependence on non-renewable energy sources, are the challenges before the attainment of clean energy goals for sustainable development. The 5-year review from the adoption of sustainable development goals (SDGs) by using bibliometric and thematic analysis was conducted in this review. This review is a synthesis of 175 scientific papers on SDG 7. Policy reforms and better funding; technology innovation and inclusion; and economic growth, rapid promotion of renewable, and alternative fuels are the recommendations for the achievement of the energy goals. Future research on energy-related goals should focus on energy justice, policy reforms, energy poverty, poor affordability, off-grid transmissions, renewable energy sources, alternative fuels, reforms in the energy supply chain, and international cooperation for better implementation of projects and for attracting foreign capital and private funds. This paper invites the attention of practitioners, academicians, funding agencies, and international agencies to collaborate in the initiatives for a clean, green, and energized world.

The influence of renewable energy usage on consumption-based carbon emissions in MINT economies

An accurate carbon emissions measurement is critical for developing an appropriate climate strategy to address ecological issues. A meaningful climate policy reaction can be offered based on trade adjusted statistics of carbon emissions. This research utilizes second-generation panel co-integration techniques to investigate the influence of globalization and renewable energy utilization on consumption-based carbon emissions (CCO₂) as well as the role of nonrenewable energy use and economic growth in the MINT-(Mexico, Indonesia, Nigeria and Turkey) countries from 1990 to 2018. The outcomes of the cross-sectional dependency and heterogeneity tests revealed slope heterogeneity and cross-sectional units across nations. Furthermore, the outcomes of the cointegration test provided evidence of a long-run association between consumption-based CO₂ emissions (CCCO₂) and the regressors. Moreover, the outcomes of both common correlated effect mean group (CCEMG) and augmented mean group (AMG) unveiled that economic growth and nonrenewable energy utilization contribute to the degradation of the environment, while globalization and renewable energy utilization help to curb the degradation of the environment. Furthermore, the outcomes of the causality test showed that all the regressors can predict CCO₂ emissions in the MINT nations. Thus, policy channeled towards globalization, economic growth, and renewable energy utilization will have a significant effect on CCO₂ emissions. Based on the study outcomes, significant policy recommendations are made for policymakers in the MINT nations.

Dynamic impacts of energy use, agricultural land expansion, and deforestation on CO2 emissions in Malaysia

This study empirically investigates the nexus among energy use, agricultural land expansion, deforestation, and carbon dioxide (CO₂) emissions in Malaysia. Time series data from 1990 to 2019 were utilized using the bounds testing (ARDL) approach followed by the Dynamic Ordinary Least Squares (DOLS) method. The DOLS estimate findings show that the energy usage coefficient is positive and significant with CO₂ emissions, indicating a 1% increase in energy consumption is related to a 0.91% rise in CO₂ emissions. In addition, the coefficient of agricultural land is positive, which indicates that agricultural land expansion by 1% is associated with an increase in CO₂ emissions by 0.84% in the long run. Furthermore, the forested area coefficient is negative, which means that decreasing 1% of the wooded area (i.e., deforestation) has a long-term effect of 5.41% increased CO₂ emissions. Moreover, the pairwise Granger causality test results show bidirectional causality between deforestation and energy use; and unidirectional causality from energy use to CO₂ emissions, agricultural land expansion to CO₂ emissions, deforestation to CO₂ emissions, agricultural land expansion to energy use, and deforestation to agricultural land expansion in Malaysia. The empirical findings reveal that increased energy use, agricultural land expansion, and deforestation have a negative impact on environmental quality in Malaysia. Thus, the effective implementation of policy measures to promote renewable energy, climate-smart agriculture, and sustainable management of forest ecosystems could be useful for reducing environmental degradation in Malaysia.

Mitigating human-induced emissions in Argentina: role of renewables, income, globalization, and financial development

Achieving environmental sustainability has become a global initiative while addressing climate change and its effects. However, the role of energy production and consumption in economic development remains critical amidst environmental pollution. Thus, the need for innovation and clean energy alternatives is critical while pursuing sustainable development. This country-specific study focuses on Argentina, where economic growth trajectory is embedded with high CO₂ emissions. This study assesses the long-term and causal impact of financial development and renewables on environmental pollution while accounting for the role of economic development and globalization using yearly data spanning 1980 to 2017. A battery of econometric methods is applied to underscore the interaction between the parameters of interest. The findings of Maki and ARDL tests of cointegration alongside Kripfganz and Schneider critical approximation p-values affirm long-run equilibrium interaction between variables. The outcomes of autoregressive distributed lag, fully modified, and dynamic ordinary least squares demonstrate that while economic expansion dampens environmental quality-globalization and renewables improve the environment. This finding suggests pollution-driven economic growth trajectory in Argentina with high dependence on fossil fuels. Besides, the gradual shift causality test finds evidence of one-way causality from renewable energy consumption, economic growth, and globalization to CO₂ emissions. Argentina's pathway in achieving sustainable development requires gradual and inclusive economic shift towards green growth.

Asymmetric Impact of International Trade on Consumption-Based Carbon Emissions in MINT Nations

The association between carbon emissions and international trade has been examined thoroughly; however, consumption-based carbon emissions, which is adjusted for international trade, have not been studied extensively. Therefore, the present study assesses the asymmetric impact of trade (import and export) and economic growth in consumption-based carbon emissions (CCO2) using the MINT nations (Mexico, Indonesia, Nigeria and Turkey) as a case study. We applied the Nonlinear ARDL to assess this connection using dataset between 1990 and 2018. The outcomes from the BDS test affirmed the use of nonlinear techniques. Furthermore, the NARDL bounds test confirmed long-run association between CCO2 and exports, imports and economic growth. The outcomes from the NARDL long and short-run estimates disclosed that positive (negative) shocks in imports increase (decrease) CCO2 emissions in all the MINT nations. Moreover, positive (negative) shocks in exports decrease (increase) CCO2 emissions in all the MINT nations. As expected, a positive shock in economic growth triggers CCO2 emissions while a negative shift does not have significant impact on CCO2 emissions in the MINT nations. Furthermore, we applied the Gradual shift causality test and the outcomes disclose that imports and economic growth can predict CCO2 emissions in the MINT nations. The study outcomes have significant policy recommendations for policymakers in the MINT nations.

The Effect of Energy Consumption and Economic Growth on Environmental Sustainability in the GCC Countries: Does Financial Development Matter?

Achieving environmental sustainability whilst minimizing the climate change effect has become a global endeavor. Hence, this study examined the effect of energy consumption, economic growth, financial development, and globalization on CO2 emissions in the Gulf Cooperation Council (GCC) countries. The research utilized a dataset stretching from 1995 to 2018. In a bid to investigate these associations, the study applied cross-sectional dependence (CSD), slope heterogeneity (SH), Pesaran unit root, Westerlund cointegration, cross-sectionally augmented autoregressive distributed lag (CS-ARDL), and Dumitrescu and Hurlin (DH) causality approaches. The outcomes of the CSD and SH tests indicated that using the first-generation techniques produces misleading results. The panel unit root analysis unveiled that the series are I (1). Furthermore, the outcomes of the cointegration test revealed a long-run association between CO2 emissions and the regressors, suggesting evidence of cointegration. The findings of the CS-ARDL showed that economic growth and energy consumption decrease environmental sustainability, while globalization improves it. The study also validated the environmental Kuznets curve (EKC) hypothesis for GCC economies. In addition, the results of the DH causality test demonstrated a feedback causality association between economic growth and CO2 emissions and between financial development and CO2 emissions. Moreover, there is a one-way causality from energy consumption and globalization to CO2 emissions in GCC economies. According to the findings, environmental pollution in GCC countries is output-driven, which means that it is determined by the amount of energy generated and consumed.

How do trade and economic growth impact environmental degradation? New evidence and policy implications from the ARDL approach

Due to various environmental degradation and natural resource depletion around the world, researchers' and policymakers' attention has turned to what causes environmental degradation. The pursuit of a healthy environment has become a global challenge, a problem that affects more than one nation. Climate change is causing severe weather conditions in every world, disrupting economies and affecting the lives of many people. Hence, the study analyzes how trade and economic growth impact environmental degradation in Belgium, the USA, and Canada using panel data from 1995 to 2016. The study utilized the autoregressive distributed lag approach to provide new evidence and policy implications. The outcome confirmed the presence of cointegration among the selected variables. However, it was observed that economic growth decreases environmental degradation in the long run while trade openness shows a positively insignificant relationship with carbon emission. Nevertheless, a positive short-run relationship was observed between economic growth and carbon emissions whereas a negatively insignificant relationship was observed for trade and carbon emission. The findings prompted policy implications that more trading could be done between the countries. When countries trade more, their economies will flourish, ensuring global prosperity and minimizing environmental degradation.

Another Look into the Relationship between Economic Growth, Carbon Emissions, Agriculture and Urbanization in Thailand: A Frequency Domain Analysis

This empirical study assesses the effect of CO2 emissions, urbanization, energy consumption, and agriculture on Thailand’s economic growth using a dataset between 1970 and 2018. The ARDL and the frequency domain causality (FDC) approaches were applied to assess these interconnections. The outcome of the bounds test suggested a long-term association among the variables of investigation. The ARDL outcomes reveal that urbanization, agriculture, energy consumption, and CO2 emissions positively trigger Thailand’s economic growth. Additionally, the frequency domain causality test was used to detect a causal connection between the series. The main benefit of this technique is that it can detect a causal connection between series at different frequencies. To the understanding of the authors, this is the first study in the case of Thailand that will apply the FDC approach to capture the causal linkage between GDP and the regressors. The outcomes of the causality test suggested that CO2 emissions, urbanization, energy consumption, and agriculture can predict Thailand’s economic growth in the long term. These outcomes have far-reaching implications for economic performance and Thailand’s macroeconomic indicators.

International Environmental Agreements and CO2 Emissions: Fresh Evidence from 11 Polluting Countries

This study attempts to evaluate the energy and carbon footprint within the framework of international environmental treaties and the efforts made by 11 large polluting countries to mitigate climate change. The econometric methodology accounts for the presence of cross-sectional dependence while it employs second-generation panel unit root tests and cointegrated relationships. To secure the robustness of our findings, we conduct an ARDL approach employing dynamic panel data techniques. Dynamic OLS is also applied to verify the validity of the empirical results. The empirical analysis supports that the reduction in CO2 emissions can be achieved without a slowdown in economic activity for the sample countries. The findings suggest insightful policy implications for policymakers and government officials.

Modeling the Dynamic Linkage between Renewable Energy Consumption, Globalization, and Environmental Degradation in South Korea: Does Technological Innovation Matter?

The present research assesses the influence of globalization and technological innovation on CO2 emissions in South Korea as well as taking into account the role of renewable energy consumption and energy consumption utilizing datasets between 1980 and 2018. The autoregressive distributed lag (ARDL) bounds testing method is utilized to assess long-run cointegration. The outcome of the ARDL bounds test confirmed cointegration among the series. Furthermore, the ARDL reveals that economic growth, energy consumption and globalization trigger environmental degradation while technological innovation improves the quality of the environment. In addition, the study employed the frequency domain causality test to capture causal linkage among the series. The major advantage of this approach is that causal linkage between series can be captured at the short, medium and long term, respectively. The outcomes of the causality test revealed that globalization, technological innovation, economic growth and energy use can predict CO2 emissions in South Korea.

Dominance of Fossil Fuels in Japan's National Energy Mix and Implications for Environmental Sustainability

Despite the drive for increased environmental protection and the achievement of the Sustainable Development Goals (SDGs), coal, oil, and natural gas use continues to dominate Japan’s energy mix. In light of this issue, this research assessed the position of natural gas, oil, and coal energy use in Japan’s environmental mitigation efforts from the perspective of sustainable development with respect to economic growth between 1965 and 2019. In this regard, the study employs Bayer and Hanck cointegration, fully modified Ordinary Least Square (FMOLS), and dynamic ordinary least square (DOLS) to investigate these interconnections. The empirical findings from this study revealed that the utilization of natural gas, oil, and coal energy reduces the sustainability of the environment with oil consumption having the most significant impact. Furthermore, the study validates the environmental Kuznets curve (EKC) hypothesis in Japan. The outcomes of the Gradual shift causality showed that CO₂ emissions can predict economic growth, while oil, coal, and energy consumption can predict CO₂ emissions in Japan. Given Japan’s ongoing energy crisis, this innovative analysis provides valuable policy insights to stakeholders and authorities in the nation’s energy sector.

Linking Economic Growth, Urbanization, and Environmental Degradation in China: What Is the Role of Hydroelectricity Consumption?

Achieving environmental sustainability has become a global initiative whilst addressing climate change and its effects. Thus, this research re-assessed the EKC hypothesis in China and considered the effect of hydroelectricity use and urbanization, utilizing data from 1985 to 2019. The autoregressive distributed lag (ARDL) bounds testing method was utilized to assess long-run cointegration, which is reinforced by a structural break. The outcome of the ARDL bounds test confirmed cointegration among the series. Furthermore, the ARDL revealed that both economic growth and urbanization trigger environmental degradation while hydroelectricity improves the quality of the environment. The outcome of the ARDL also validated the EKC hypothesis for China. In addition, the study employed the novel gradual shift causality test to capture causal linkage among the series. The advantage of the gradual shift causality test is that it can capture gradual or smooth shifts and does not necessitate previous information of the number, form of structural break(s), or dates. The outcomes of the causality test revealed causal connections among the series of interest.

Effect of Two Different Heat Transfer Fluids on the Performance of Solar Tower CSP by Comparing Recompression Supercritical CO2 and Rankine Power Cycles, China

China intends to develop its renewable energy sector in order to cut down on its pollution levels. Concentrated solar power (CSP) technologies are expected to play a key role in this agenda. This study evaluated the technical and economic performance of a 100 MW solar tower CSP in Tibet, China, under different heat transfer fluids (HTF), i.e., Salt (60% NaNO3 40% KNO3) or HTF A, and Salt (46.5% LiF 11.5% NaF 42% KF) or HTF B under two different power cycles, namely supercritical CO2 and Rankine. Results from the study suggest that the Rankine power cycle with HTF A and B recorded capacity factors (CF) of 39% and 40.3%, respectively. The sCO2 power cycle also recorded CFs of 41% and 39.4% for HTF A and HTF B, respectively. A total of 359 GWh of energy was generated by the sCO2 system with HTF B, whereas the sCO2 system with HTF A generated a total of 345 GWh in the first year. The Rankine system with HTF A generated a total of 341 GWh, while the system with B as its HTF produced a total of 353 GWh of electricity in year one. Electricity to grid mainly occurred between 10:00 a.m. to 8:00 p.m. throughout the year. According to the results, the highest levelized cost of energy (LCOE) (real) of 0.1668 USD/kWh was recorded under the Rankine cycle with HTF A. The lowest LCOE (real) of 0.1586 USD/kWh was obtained under the sCO2 cycle with HTF B. In general, all scenarios were economically viable at the study area; however, the sCO2 proved to be more economically feasible according to the simulated results.

Investigating the Linkage between Economic Growth and Environmental Sustainability in India: Do Agriculture and Trade Openness Matter?

This paper assesses the linkage between CO2 emissions and economic growth while taking into account the role of energy consumption, agriculture, and trade openness in India. Using data covering the period between 1965 and 2019, the Bayer and Hanck cointegration and Gradual shift causality tests are applied to assess these economic indicators relationships’. Furthermore, we employed the wavelet coherence test. The advantage of the wavelet coherence test is that it differentiates between short-, medium-, and long-run dynamics over the entire sampling period. To the best of the authors’ understanding, the present paper is the first to apply wavelet analysis to investigate this relationship by incorporating agriculture as a determinant of environmental degradation. The empirical outcomes show that all variables appear to be highly correlated with CO2 emissions with the exemption of trade openness. This is further affirmed by the Gradual shift causality test, which shows that agriculture and energy consumption are crucial determinants of CO2 emissions in India. Accordingly, adequate policy measures are proposed based on these findings.

Sustainability of Energy-Induced Growth Nexus in Brazil: Do Carbon Emissions and Urbanization Matter?

This study assesses the relationship between economic performance and environmental sustainability by taking into account the role of energy consumption, urbanization, and trade openness in Brazil by using data spanning from 1965 to 2019. The study is distinct from previously documented studies in literature in terms of scope for Brazil, where few entries have been recorded. The major objectives are to address the questions: (a) Is there a long-run connection between the variables under consideration? (b) Can CO2 emissions, trade openness, and energy consumption predict economic performance of Brazil? (c) What is the connection between economic growth and the independent variables at different frequencies and time-period? Furthermore, the study utilized dynamic ordinary least square (DOLS), fully modified ordinary least square (FMOLS), Maki Cointegration, and autoregressive distributed lag (ARDL) to capture the long-run association between the variables of interest. Also, we used the Wavelet coherence and Gradual-shift causality tests to capture the causal linkage between economic growth and the regressors. The advantage of the wavelet coherence test is that it can capture causal linkage between series at different frequencies and periods. The outcome of both Maki cointegration and ARDL bounds testing to cointegration affirms the presence of long-run interaction among the parameters of interest. Furthermore, the outcomes of the DOLS and FMOLS revealed that energy consumption, CO2 emissions, and urbanization exert positive impacts on economic growth in Brazil while there is no significant connection between trade openness and economic growth. Moreover, Gradual shift causality test outcomes disclosed that urbanization, trade openness, CO2 emissions and energy usage can predict the economic performance of Brazil. The outcomes of the wavelet coherence test give credence to the FMOLS, DOLS, and Gradual shift causality tests.