Analysis of nighttime aerosols and relation to covariates over a highly polluted sub-Saharan site using Mann-Kendall and wavelet coherence approach.

High emissions of aerosols and trace gases during nighttime can cause serious air quality, climate, and health issues, particularly in extremely polluted cities. In this paper, an effort has been made to examine the variations in aerosols and trace gases over a sub-Saharan city of Ilorin (Nigeria) during nighttime. We have used Aerosol Robotic Network data of aerosol optical depth (AOD) at 500 nm, Angstrom exponent (AE) (440/870), and precipitable water (WVC). Both AE and WVC showed a decreasing trend of -0.0012% and -0.0010% per year, respectively. We also analyzed nighttime data of carbon monoxide (CO), methane (CH4 ), and ozone (O3 ) from Atmospheric Infrared Sounder and aerosol subtypes from CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation). AOD, AE, and WVC average values are found to be 0.64 ± 0.33, 0.74 ± 0.24, and 3.40 ± 0.97, respectively. As a result of northeasterly winds carrying Saharan dust during the dry season, the greatest value of AOD (1.29) was observed in February. Desert dust aerosols (37.63%) were the most prevalent type, followed by mixed aerosols (44.15%). Winds at a height of 1500 m above ground level were likely transporting Saharan dust to Ilorin. CALIPSO images revealed that Ilorin's atmosphere contained dust, polluted continental, clean maritime, and polluted dust on high AOD days. The National Oceanic and Atmospheric Administration's vertical sounding profiles showed that the presence of high AOD values was caused by the inversion layer trapping aerosol pollution. Average nighttime concentrations of CO, O3 , and CH4 were measured to be 127 ± 18, 29.7 ± 2.1, and 1822.6 ± 12.7 ppbv, respectively. The wavelet coherence spectra exhibited significant quasi-biannual and quasi-annual oscillations at statistically significant levels.

The role of energy, political stability, and real income on achieving carbon neutrality: asymmetric evidence.

Apart from business considerations stemming from the marketplace, businesses, individuals, and the economy at large, political decisions also play a role on environmental quality. Governments make a series of policies that impact private businesses, sectors, the environment, and the economy at large. In this paper, we test the asymmetric role of political risk on CO2 emissions, while controlling for renewable energy, non-renewable energy, and real income: policy toward environmental sustainability objectives in the context of Turkey. To realize the motive of this study, we capture the asymmetric effect of the regressors by adopting the nonlinear autoregressive distributed lag method (NARDL). This research adds to the environmental literature in terms of methodological and empirical. Methodologically, the study shows that a nonlinear relationship exists among the variables, and it has a significant impact on environmental sustainability targets. The outcome of the NARDL indicates that the increasing political risk, non-renewable energy, and economic growth follow a trajectory trend on carbon emissions, which is unsustainable in Turkey, but renewable energy is sustainable. Moreover, decreasing real income and non-renewable energy decreases carbon emissions. This research also deployed the frequency domain test to capture the causal association of the concerned variables and the outcome indicates political risk, renewable energy, non-renewable energy use, and real income are predictors of CO2 in Turkey. From this result, policies geared toward promoting a sustainable environment were formulated.

Blockchain technology-based FinTech banking sector involvement using adaptive neuro-fuzzy-based K-nearest neighbors algorithm.

The study aims to investigate the financial technology (FinTech) factors influencing Chinese banking performance. Financial expectations and global realities may be changed by FinTech's multidimensional scope, which is lacking in the traditional financial sector. The use of technology to automate financial services is becoming more important for economic organizations and industries because the digital age has seen a period of transition in terms of consumers and personalization. The future of FinTech will be shaped by technologies like the Internet of Things, blockchain, and artificial intelligence. The involvement of these platforms in financial services is a major concern for global business growth. FinTech is becoming more popular with customers because of such benefits. FinTech has driven a fundamental change within the financial services industry, placing the client at the center of everything. Protection has become a primary focus since data are a component of FinTech transactions. The task of consolidating research reports for consensus is very manual, as there is no standardized format. Although existing research has proposed certain methods, they have certain drawbacks in FinTech payment systems (including cryptocurrencies), credit markets (including peer-to-peer lending), and insurance systems. This paper implements blockchain-based financial technology for the banking sector to overcome these transition issues. In this study, we have proposed an adaptive neuro-fuzzy-based K-nearest neighbors' algorithm. The chaotic improved foraging optimization algorithm is used to optimize the proposed method. The rolling window autoregressive lag modeling approach analyzes FinTech growth. The proposed algorithm is compared with existing approaches to demonstrate its efficiency. The findings showed that it achieved 91% accuracy, 90% privacy, 96% robustness, and 25% cyber-risk performance. Compared with traditional approaches, the recommended strategy will be more convenient, safe, and effective in the transition period.

Does the potency of economic globalization and political instability reshape renewable energy usage in the face of environmental degradation?

Since renewable energy is essentially non-carbohydrate in nature, it can generate little or no pollutants and can therefore help in achieving both sustainable development and environmental quality. In this regard, the question that continues to persist is whether economic growth, economic globalization, and political risk can potentially affect renewable energy in the presence of environmental deterioration. In this context, the current research provides evidence to support this theoretical context by investigating the impact of economic globalization, economic growth environmental degradation, and political risk, on the usage of renewable energy in Vietnam using a dataset spanning the period between 1984 and 2019. For empirical analysis, the dynamic autoregressive distributed lag approach is utilized. Based on our analysis, economic growth positively impacts renewable energy in the long and short term. Economic globalization also positively affects renewable energy in the long term, but a neutral impact is uncovered in the short term. Political risk and environmental degradation are adversely related to renewable energy in the short and long run. The findings from the frequency domain approach reveal a causal interaction from political risk to renewable energy, and from renewable energy to economic globalization, whereas a feedback causal interaction is discovered between renewable energy and environment degradation, as well as between economic growth and renewable energy. From a policy standpoint, we propose that the Vietnamese policymakers need to consider economic globalization as a renewable energy promotion tool via capital inflow, foreign direct investment, and technological transfer.

Asymmetric effect of structural change and renewable energy consumption on carbon emissions: designing an SDG framework for Turkey.

A plethora of studies have shown that structural change helps nations achieve socioeconomic growth. The influence of structural change on environmental quality, on the other hand, has yet to be thoroughly investigated. As a result, the current study assesses the asymmetric impact of structural change on CO2 emissions while controlling for the effects of economic progress, renewable energy utilization, and nonrenewable energy in Turkey. To this end, this research used yearly data stretching from 1965 to 2019. The study applied several econometric approaches including nonlinear auto-regressive distributed lag (NARDL) and spectral causality to assess these associations. The outcomes from the NARDL reveal that variations in the regressors have a nonlinear influence on CO2 in Turkey. Moreover, the transition in the economy's structure helps to boost ecological quality, while the findings also show that Turkey's current economic progress trajectory is unsustainable due to the country's reliance on fossil fuel-based energy consumption. The outcomes of the spectral causality test also show that structural change can predict CO2 emissions in Turkey at different frequencies. Based on the study findings, the government should encourage investment in the service sector in order to maintain a suitable level of environmental sustainability.

The nexus between environmental strategy and environmental performance: analyzing the roles of green product innovation and mechanistic/organic organizational structure.

The relationship between environmental strategy and environmental performance has been extensively analyzed in the environmental management literature. However, this relationship is spurious due to the inconsistence outcomes, lack of intervening mechanism, and scarcity of appropriate context. This study undertakes these considerations by exploring the underlying moderation-mediation mechanism through which proactive corporate environmental strategy affects corporate environmental performance. The hypotheses of the study were empirically tested on the data gathered from 147 ISO 14001:2015 certified firms in Pakistan. The data was statistically validated and then tested with Bootstrapping method using Preacher and Hayes Process Macros. The findings of the study revealed that a proactive corporate environmental strategy predicts corporate environmental performance through green product innovation. Moreover, the moderation hypothesis of the organizational structure variable in the nexus between proactive corporate environmental strategy and green product innovation was not supported in the full sample, whereas the split sample based on organizational size indicated moderation effects in the small firm's sample. The findings of the study carry important implications for firms related to corporate environmental strategy and green product innovation strategy.

Environmental R&D and trade-adjusted carbon emissions: evaluating the role of international trade.

In the contemporary era, it is evident that consumption-based carbon emissions (CCO2e), adjusted for international trade, are a more accurate and robust measure of environmental pollution than production-based emissions. Therefore, many studies have focused on exploring the determinants of CCO2e; however, the literature could not yet discern environment-related R&D budget (ERRD) and political risk index (PRI) as a new driver. To fill this gap, the current paper aims to divulge the dynamic effects of ERRD and PRI on CCO2e while taking imports, exports, and GDP as control regressors. To do so, the G7 nations' data from 1990 to 2020 is utilized, and several advanced econometric tests and techniques are deployed to tackle the advanced issues (i.e., cross-section dependence, heterogeneity, and endogeneity) in econometrics. The CS-ARDL estimates suggest that PRI and ERRD significantly lessen the environmental quality by disrupting the detrimental effects of CCO2e. Likewise, the rise in exports possesses a negative association with the ratio of CCO2e. However, CCO2e significantly tends to surge on account of an increase in GDP and imports. GDP squared exhibits the negative link with CCO2e, confirming the EKC hypothesis in G7 nations. Besides, the AMG technique and causality test validate the robustness of our findings. In addition, the policies related to CCO2e by authorities will take approximately more than a year to absorb their effects.

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.

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.

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.

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.

The role of economic complexity in the environmental Kuznets curve of MINT economies: evidence from method of moments quantile regression.

In the face of mounting climate change challenges, reducing emissions has emerged as a key driver of environmental sustainability and sustainable growth. Despite the fact that research has been conducted on the environmental Kuznets curve (EKC), few researchers have analyzed this in the light of economic complexity. Thus, the current research assesses the effect of economic complexity on CO2 emissions in the MINT nations while taking into account the role of financial development, economic growth, and energy consumption for the period between 1990 and 2018. Using the novel method of moments quantile regression (MMQR) with fixed effects, an inverted U-shape interrelationship is found between economic growth and CO2 emissions, thus validating the EKC hypothesis. Energy consumption and economic complexity increase CO2 emissions significantly from the 1st to 9th quantiles. Furthermore, there is no significant interconnection between financial development and CO2 emissions across all quantiles (1st to 9th). The outcomes of the causality test reveal a feedback causal connection between economic growth and CO2, while a unidirectional causality is established from economic complexity and energy use to CO2 emissions in the MINT nations. Based on the findings, we believe that governments should stimulate the financial sector to provide domestic credit facilities to industrialists, investors, and other business enterprises on more favorable terms so that innovative technologies for environmental protection can be implemented with other policy recommendations.

The asymmetric effects of renewable energy consumption and trade openness on carbon emissions in Sweden: new evidence from quantile-on-quantile regression approach.

With the passage of time, the continued burning of fossil fuels is proving to be one of the world's most serious issues. In response, the current research aims to assess the critical linkage between carbon emissions and renewable energy, trade openness, and economic growth in Sweden utilizing a dataset from 1965 to 2019. The study applied the novel quantile-on-quantile regression (QQ) approach to assess this relationship. The main objectives are to address the following questions: (i) What are the effects of trade openness on CO2 emissions in each quantile? (ii) Does renewable energy consumption mitigates CO2 emissions in each quantile? What is the impact of economic growth on CO2 emissions in each quantile? The outcomes from the QQ approach revealed that at low and medium quantiles (0.1-0.6), the effect of trade openness on CO2 emissions is negative. Furthermore, at lower and higher quantiles (0.1-0.90) of combination of renewable energy consumption and CO2 emissions, the effect of renewable energy consumption on CO2 emissions is negative. Finally, at majority of the quantiles, the effect of economic growth on CO2 emissions is negative. Moreover, the present study applied the quantile regression (QR) approach as a robustness check. The findings of the QR validate the findings of the QQR approach. The study proposes that policy-makers in Sweden should place greater emphasis on raising public awareness regarding the issues of renewable energy since it mitigates environmental degradation.

Does renewable energy electricity and economic complexity index help to achieve carbon neutrality target of top exporting countries?

Despite extensive studies into international trade and CO2 pollution, a panel of only top exporting economies was not considered. As the current research is an endeavor to address the gap by exploring the impact of economic complexity index (ECI) and renewable energy electricity (RELC) on consumption-based carbon emissions (CCO2) in the presences of exports, imports, and gross domestic product (GDP) in the top exporting countries from 1990 to 2019. The results confirm a relationship between consumption-based carbon emissions, economic complexity index, renewable energy electricity, exports, imports, and economic growth in both the short-run and long run. Empirical evidence for cross-sectional auto-regressive distributed lags (CS-ARDL) estimates, confirms that economic complexity index imports and GDP are positively associated and have significant adverse short-run and long-run impacts on consumption-based carbon emission. Whereas, export and renewable energy electricity significantly reduce carbon emissions. To achieve carbon neutrality target, policymakers should make economic complexity reforms, import green products, and promote investments in sustainable sources.

Linking Innovative Human Capital, Economic Growth, and CO2 Emissions: An Empirical Study Based on Chinese Provincial Panel Data.

To study the economic and environmental effects of human capital, previous studies measure human capital based on education; however, this approach has many shortcomings because not all educated people are innovative human capital. Hence, this study introduces the concept of innovative human capital by developing a new index that measures human capital based on the number of patents every one million R&D staff full-time equivalent. After this, this paper studies the impact of innovative human capital on CO2 emissions in China. The provincial panel data of 30 Chinese provinces from 2003 to 2017 is analyzed using the fixed effect, ordinary least squares, and the system generalized method of moments (SYS-GMM). The analysis revealed that innovative human capital alleviates environmental deterioration in China. The findings unfold the existence of the environmental Kuznets curve (EKC) considering innovative human capital in the model. It implies that Chinese economic development will eventually support environmental sustainability if China continues to develop its innovative human capital. Among the control variables, economic structure, population density, and energy intensity stimulate environmental degradation by increasing CO2 emissions. However, FDI has a negative relationship with CO2 emissions. Lastly, the study proposes comprehensive policies to increase innovative human capital for environmental sustainability.

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.

Implications of Governance, Natural Resources, and Security Threats on Economic Development: Evidence from Sub-Saharan Africa.

Sub-Saharan African countries are known to be bedeviled with some challenges hindering the economic development. Meanwhile, some of these issues have not been exhaustively investigated in the context of the region. Thus, this study aimed at investigating the implications of government effectiveness, availability of natural resources, and security threats on the regions' economic development. Yearly data, spanning from 2007 to 2020, was converted from low frequency (yearly) to high frequency (quarterly) and utilized. Data analysis was conducted using Dynamic heterogeneous panel level estimators (PMG and CS-ARDL). Findings show that while PMG estimator confirms a long-run causal effect of governance, natural resources, and security threats on economic development, only natural resources show a short-run causal effect with economic development, while the CS-ARDL (model 2) confirms the significance of all the variables both in the long and short-run. Moreover, the ECT coefficients for both models were found to be statistically significant at less than 1% significance level, which indicates that the systems return back to equilibrium in case of a shock that causes disequilibrium, and in addition, reveals a stable long-run cointegration among the variables in the model. Finally, this study suggests that the policy makers in SSA countries should place more emphasis on improving governance, managing security challenges, and effectively utilizing rents from the natural resources, as all these have severe implications for the economic development of the region if not addressed.

Does environmental taxes achieve the carbon neutrality target of G7 economies? Evaluating the importance of environmental R&D.

The present study highlights the importance of environmental taxes and R&D in achieving the goal of carbon neutrality. Post Paris conference (COP21), countries set domestic targets to achieve zero carbon or carbon neutrality. Several studies have been conducted to explore the factors affecting environmental quality. However, the literature on the importance of environmental taxes and environmental R&D in affecting environmental quality is scant, and thus, this study investigates the impact of environmental taxes and R&D on consumption-based carbon emissions for G-7 countries over a period of 1990-2019. The cointegration test results show a stable long-run association between environmental taxes, environmental R&D, imports, exports, GDP, and consumption-based CO2 emissions. The results show that in the short- and long-run, environmental taxes, environmental R&D, and exports significantly reduce carbon emissions, whereas GDP and imports significantly enhance carbon emissions. The Dumitrescu and Hurlin Granger causality test results show that any policy that targets environmental taxes, environmental R&D, exports, imports, and GDP significantly changes CO2 emissions. This study recommends that policymakers in G-7 countries should focus on environmental R&D and taxes to achieve the goal of carbon neutrality.

Do financial regulations matters for sustainable green economy: evidence from Turkey.

The attention of scholars and policymakers on the achievement of sustainable green economy has been on increase; however, the topic has not been exhaustively investigated. This study empirically investigates the implications of financial regulations on sustainable green economy in Turkey utilizing a time series data spanning from 1996 to 2019. This study employed Perron and Lee-Strazicich unit root test in the presence of structural break point for examining the stationarity properties of the series and FMOLS, CCR, and ARDL for estimating the long and short-run effect of the financial regulations on carbon productivity. Our study demonstrates that rule of law, economic freedom, and inflation have a significant long-run relationship with carbon productivity as confirmed by FMOLS and CCR, while rule of law, regulatory quality economic freedom, and inflation were confirmed by ARDL to have long-run causal relationship with carbon productivity. In addition, our study found that control of corruption, government effectiveness, rule of law, regulatory quality economic freedom, and inflation have a short-run causal effect on carbon productivity. Finally, this study concludes that financial regulations is significant for achieving sustainable green economy in Turkey and as such should be accorded adequate attention by the policy makers.