Do renewable energies contribute to enhancing environmental quality in Eastern Africa?

East Africa has enormous renewable energy potential, but only a small portion of it has been exploited, and little is known on its role in improving environmental quality. Thus, this study empirically examines the impact of renewable energy on the environment using ecological footprint (EF; positive indicator) and CO₂ emissions (negative indicator) as proxy indicators for environmental quality in a panel of ten East African countries from 1990 to 2015. These indicators were chosen due to their potential impact in the environment. The work used the pooled mean group (PMG) as the main panel estimator to determine the impact while controlling non-renewable energy consumption, GDP per capita, and foreign direct investment (FDI). PMG has been used as it forces the long-run coefficients to be equal across all panel groups. The findings show that in the long run, there is a significant negative relationship between CO₂ emissions and renewable energy consumption, as well as a significant positive relationship (with a low impact) between EF and renewable energy consumption, suggesting that renewable energy use enhances the area’s environmental quality. Also, results indicate that non-renewable energy use degrades environmental quality in both metrics, whereas GDP degrades environmental quality through CO₂ emissions and improves environmental quality through EF. This requires East African countries to focus a higher emphasis on accessible renewable energy sources to achieve quick and sustainable economic growth and minimize environmental effects. To accomplish this, strategic policies and legislation, as well as the promotion of green technology, are required.

     

Carbon dioxide emissions,output, and energy consumption categories in Algeria

This study examines the relation between CO₂ emissions, income, non-renewable, and renewable energy consumption in Algeria during the period extending from 1980 to 2011. Our work gives particular attention to the validity of environmental Kuznets curve (EKC) hypothesis. The autoregressive distributed lag (ARDL) with break point method outcome demonstrates the positive effect of non-renewable type of energy on CO₂ emissions consumption. On the contrary, the results reveal an insignificant effect of renewable energy on environment improvement. Moreover, the results accept the existence of EKC hypothesis but the highest gross domestic product value in logarithm scale of our data is inferior to the estimated turning point. Consequently, policy-makers in Algeria should expand the ratio of renewable energy and should decrease the quota of non-renewable energy consumption.     

The impact of environment degrading factors and remittances on health expenditure: an asymmetric ARDL and dynamic simulated ARDL approach

This paper investigates the impact of CO₂ emissions, air pollution (PM2.5) exposure, foreign remittances, energy consumption, renewable energy consumption, trade openness, and gross domestic product per capita on health expenditure in a panel of the 27 highest emitting countries from 2000 to 2019. Focusing on objectives, panel ARDL, and dynamic simulated ARDL models are used to examine the short-run and long-run impact of the variables on health expenditure. An asymmetric or nonlinear ARDL model is used to test the asymmetric effect of CO₂ emissions, air pollution exposure, and foreign remittance inflows on health expenditure. The results show that environment-degrading factors, remittances, and GDP per capita significantly impact health expenditure. There is an asymmetric effect of remittances, CO₂ emissions, and air pollution (PM2.5) exposure on health expenditure. Based on the results, the study suggests policymakers should make policies regarding environment-degrading elements as these factors cause huge increases in health spending in a country. Consumption of renewable energy helps reduce health expenditure as it does not cause environmental degradation, irrespective of other forms of energy, and it is suggested that policies relating to foreign remittance inflows should be encouraged and made efficient.

     

Influencing factors of carbon emissions and their trends in China and India: a machine learning method

China and India are the largest coal consumers and the most populated countries in the world. With industrial and population growth, the need for energy has increased, which has inevitably led to an increase in carbon dioxide (CO₂) emissions because both countries depend on fossil fuel consumption. This paper investigates the impact of energy consumption, financial development (FD), gross domestic product (GDP), population, and renewable energy on CO₂ emissions. The study applies the long short-term memory (LSTM) method, a novel machine learning (ML) approach, to examine which influencing driver has the greatest and smallest impact on CO₂ emissions; correspondingly, this study builds a model for CO₂ emission reduction. Data collected between 1990 and 2014 were analyzed, and the results indicated that energy consumption had the greatest effect and renewable energy had the smallest impact on CO₂ emissions in both countries. Subsequently, we increased the renewable energy coefficient by one and decreased the energy consumption coefficient by one while keeping all other factors constant, and the results predicted with the LSTM model confirmed the significant reduction in CO₂ emissions. Finally, this study forecasted a CO₂ emission trend, with a slowdown predicted in China by 2022; however, CO₂ emission’s reduction is not possible in India until 2023. These results suggest that shifting from nonrenewable to renewable sources and lowering coal consumption can reduce CO₂ emissions without harming economic development.

     

Do transportation taxes promote pro-environmental behaviour? An empirical investigation

The transportation sector is a crucial driver of energy intensity and environmental degradation. Therefore, we aim to explore the nexus of transportation taxes, energy intensity, and CO₂ emissions for the BICS economies. The econometric approaches, CS-ARDL and PMG-ARDL, have been employed to compute the estimates. The long-run estimates of the green transportation tax variable are negatively significant in both energy intensity and CO₂ emissions models irrespective of the estimation technique. These findings imply that green transportation taxes help reduce energy intensity and CO₂ emissions in BICS economies. Conversely, in the short-run, the effects of transportation taxes on energy intensity and CO₂ emissions are mixed and inconclusive. Hence, transportation taxes are necessary to keep the polluters under control not only from the transport sector but also serve as a deterrent for other sectors as well.

     

Effects of urbanization and nonrenewable energy on carbon emission in Africa

This study investigates the impact of urbanization and nonrenewable energy consumption on carbon emissions. The context of the analysis is 54 African Union countries from 1996 to 2019. For estimation, we use panel quantile regression (PQR) and fully modified ordinary least squares (FMOLS). Our regression results demonstrate that there is a positive correlation between urbanization and CO₂ emission. Further, our empirical results confirmed that nonrenewable energy consumption increases environmental pollution in African Union countries. The outcomes demonstrate the EKC hypothesis because at the initial stage of development, when economic growth increases, environmental pollution increases; after a threshold point, environmental pollution decreases as economic growth increases. It can find an inverted U-shaped relationship between economic growth and CO₂ emission. The findings also show that urbanization should be planned; otherwise, it can lead to environmental degradation in the long run. Africa continent takes strict action and builds a blueprint for efficient and effective energy production and consumption. The only solution to achieve green growth in Africa is to shift from fossil fuel energy supply to renewable energy supply.

     

Renewable energy and greenhouse gas emissions from the waste sectors of European Union member states: a panel data analysis

In the last two decades, there has been a rich debate about the environmental degradation that results from exposure to solid urban waste. Growing public concern with environmental issues has led to the implementation of various strategic plans for waste management in several developed countries, especially in the European Union. In this paper, the relationships were assessed between economic growth, renewable energy extraction and greenhouse gas (GHG) emissions in the waste sector. The Environmental Kuznets Curve hypothesis was analysed for the member states of the European Union, in the presence of electricity generation, landfill and GHG emissions for the period 1995 to 2012. The results revealed that there is no inverted-U-shaped relationship between income and GHG emissions in European Union countries. The renewable fuel extracted from waste contributes to a reduction in GHG, and although the electricity produced also increases emissions somewhat, they would be far greater if the waste-based generation of renewable energy did not take place. The waste sector needs to strengthen its political, economic, institutional and social communication instruments to meet its aims for mitigating the levels of pollutants generated by European economies. To achieve the objectives of the Horizon 2020 programme, currently in force in the countries of the European Union, it will be necessary to increase the share of renewable energy in the energy mix.     

Does energy consumption contribute to environmental pollutants? evidence from SAARC countries

The objective of the study is to examine the causal relationship between energy consumption and environmental pollutants in selected South Asian Association for Regional Cooperation (SAARC) countries, namely, Bangladesh, India, Nepal, Pakistan, and Srilanka, over the period of 1975–2011. The results indicate that energy consumption acts as an important driver to increase environmental pollutants in SAARC countries. Granger causality runs from energy consumption to environmental pollutants, but not vice versa, except carbon dioxide (CO₂) emissions in Nepal where there exists a bidirectional causality between CO₂ and energy consumption. Methane emissions in Bangladesh, Pakistan, and Srilanka and extreme temperature in India and Srilanka do not Granger cause energy consumption via both routes, which holds neutrality hypothesis. Variance decomposition analysis shows that among all the environmental indicators, CO₂ in Bangladesh and Nepal exerts the largest contribution to changes in electric power consumption. Average precipitation in India, methane emissions in Pakistan, and extreme temperature in Srilanka exert the largest contribution.     

A global prospective of environmental degradations: economy and finance

Finance plays a crucial role in a fast-growing economy that can lead to environmental degradation. The present study utilizes balanced panel data of 105 countries for the time span 1980–2016 to investigate empirical linkage among environmental degradations: economy and finance. It also unfolds the nonlinear impact of economy and finance on environmental degradation. Existing literature on environmental issues mainly focuses on individual case studies uncovering particular regions, but the comprehensive analysis is not available. To fill this gap, panels were classified into five divisions: global, regional, income-based, OECD-based, and carbon emission. The cross-sectional dependence test is applied to identify the degree of cross-sectional dependence among concerned 16 divisions. The second-generation panel models (CADF and Westerlund cointegration, DOLS, and DH heterogenous causality) are employed on a sample set to compute to unit root, cointegration, and long-run and short-run dynamics among concerned variables, respectively. The findings infer the inverted EKC and U-shaped EKC in 10 and 3 out of 16 divisions with respect to environmental degradation—economy nexus, respectively, while 8 and 2 out of 16 divisions indicate the inverted EKC and U-shaped EKC, respectively, in terms of environmental degradation—finance nexus. In 12 out of 16 divisions, the energy consumption uplifts the CO₂ emissions. The DH causality affirmed a bidirectional causality among economy, finance, and energy consumption, respectively.

     

Comparative analysis of the growth impact of pollution and energy use in selected West African nations

We adopt the FMOLS and Granger causality technique to analyse the effect of energy use and carbon emissions on output growth in selected West African economies, which includes Nigeria, Gambia and Ghana, from 1970 to 2019. Findings confirm that energy use enhances growth in the three selected West African economies. But in terms of significance, energy consumption is significant in Nigeria and Gambia at a 1% level of significance while it is insignificant for the Gambia. CO₂ emission positively and significantly propels economic growth for the three selected West African economies. For Nigeria, causality evidence shows no direct influence among the variables. For Ghana, we find a bi-causal association between output growth and carbon emissions and a unidirectional causality from pollution to energy consumption. For Gambia, economic growth causes CO₂ emissions. We recommend that the West African government reinforce their stand on a sustainable growth path through energy conservation.

     

How to bend down the environmental Kuznets curve: the significance of biomass energy

Sources of renewable energy have received wide attention in the literature because of serious threats to the environment. However, some renewable resources, including biomass energy role is debatable in the energy economics literature. This empirical work focuses to analyze the role of biomass energy in carbon dioxide (CO₂) emissions using the framework of the environmental Kuznets curve (EKC) in Pakistan over the period from 1980 to 2015. The bound testing approach suggests there is cointegration among study variables. The study uses an auto-regressive distributed lag model (ARDL) with a structural break in the series. To summarize the findings of the study, it can be inferred that biomass energy increase CO₂ emissions. In addition, biomass energy helps to form a U-shaped relationship between income and CO₂ emissions that support the EKC hypothesis. Also, the feedback hypothesis is found between biomass energy and CO₂ emissions. The findings would guide policymaker with practical guidelines to formulate policies to utilize a high amount of biomass energy in a sustainable manner.

     

The effects of economic growth and innovation on CO2 emissions in different regions

Economic growth and economic energy consumption have received greater attention due to its contribution to global CO₂ emissions in recent decades. The literature on CO₂ emissions and innovation for regional differences is very scanty as there is not enough study that considered different regions in a single analysis. We adopt a holistic approach by incorporating different regions so as to assess how innovation contributes to emission reduction. The study, therefore, examined the effects of innovation and economic growth on CO₂ emissions for 18 developed and developing countries over the period of 1990 to 2016. The study used panel technique capable of dealing with cross-section dependence effects: panel cross-sectional augmented Dickey-Fuller (CADF) unit root to determine the order of integration, Westerlund cointegration tests confirmed that the variables are co-integrated. We employed panel fully modified ordinary least square (FMOLS) and panel dynamic ordinary least square (DOLS) to estimate the long-run relationship. The results show that energy consumption increases CO₂ emissions at all panel levels. However, innovation reduces CO₂ emissions in G6 while it increases emissions in the MENA and the BRICS countries. Environmental Kuznets curve (EKC) hypothesis is valid for the BRICS. The pollution haven hypothesis (PHH) and pollution halo effect were confirmed at different panel levels. Based on the findings different policy recommendations are proposed.

     

The nexus between remittances,natural resources,technological innovation,economic growth,and environmental sustainability in Pakistan

Globally, the issues about sustainable development are on the increase. Moreover, these issues are rising every day in Pakistan, as remittances are increasing, technology innovation is ambiguous, natural resources are degraded, and economic expansion might pose serious challenges to the environment. Thus, this research looks at how remittances, natural resources, technological innovation, and economic growth affect carbon dioxide (CO₂₎ emissions in Pakistan by controlling energy consumption and urbanization from 1990 to 2019. The Bayer and Hanck test of combined cointegration discloses a cointegration between remittances, natural resources, technological innovations, economic growth, and CO₂ emissions. Moreover, the autoregressive distributive lag model (ARDL) proposes a significant positive association between remittances and CO₂ emissions in the long run, indicating that the increase in remittances distresses the environmental performance of Pakistan. Our study confirms that natural resources decrease CO₂ emissions while technological advancement, economic progress, energy use, and urbanization increase CO₂ emissions. In addition, the results of robustness checks by employing fully modified ordinary least squares and dynamic ordinary least squares are parallel to the conclusions of ARDL estimations. Furthermore, the frequency causality test results show that remittances, natural resources, technological innovation, economic growth, energy use, and urbanization cause CO₂ emissions at different frequencies. Therefore, to achieve the sustainable development goals, appropriate policy repercussions can be developed toward advanced and environmentally sustainable sources of energy.

     

Policy insight from renewable energy,foreign direct investment (FDI), and urbanization towards climate goal: insight from Indonesia

This study is premised on Indonesia’s climate goal amidst good economic performance. To test the environmental implication of this macroeconomic performance of Indonesia, we adopt Indonesian quarterly data of 1990Q1–2018Q4 for empirical analysis. Relevant instruments in the economic performance of Indonesia such as urbanization, foreign direct investment (FDI), and renewable energy source are all adopted for accurate estimations and analysis of this topic. Different approaches (structural break test, autoregressive distributed lag (ARDL)-bounds testing and Granger causality) are all adopted in this study. Our analysis and policy recommendations are based on the short-run and long-run ARDL dynamics and Granger causality. Findings from ARDL confirmed negative relationship between carbon emission and renewable energy source, FDI, and urbanization. Also, a U-shape instead of inverted U-shaped EKC is found confirming the impeding implication of Indonesian economic growth to its environmental performance if not checkmate. From Granger causality analysis, all the variables are seen transmitting to urbanization in a one-way causal relationship. Also, FDI and renewable energy prove to be essential determinants of the country’s environment development; hence, FDI is seen transmitting to both energy sources (fossil fuels and renewables) in a one-way causal relationship. Renewable energy is as well seen having two ways causal relationship with both carbon emission and fossil fuels. This result has equally exposed the significant position of the three instruments (urbanization, FDI, and renewable energy source) in Indonesian environment development.

     

Influence of tourism,governance, and foreign direct investment on energy consumption and CO2 emissions: a panel analysis of Muslim countries

The empirical linkages from tourism, governance, and FDI have been quantified on CO₂ emission and energy use over 2002–2014 for a panel of 13 Muslim countries. To this end, we have examined the data for cross-sectional dependence (CD) and panel heterogeneity and employed panel algorithms, which account for both CD and panel heterogeneity. The results from Pedroni, Westerlund, and Kao tests supported the existence of a cointegration association between the chosen variables. In the CO₂ model, we observed that tourism positively, and governance negatively, influences the CO₂ emission. However, in the case of the energy model, the results of tourism pose a negative relationship, and governance indicates a positive relationship with energy use. The results supported the pollution haven phenomenon, finance, and energy triggered pollution in the study area. Further, the research supported a two-way causality between tourism and CO₂, where there is a unilateral causality from governance to CO₂. Similarly, a unidirectional causality was obtained from energy towards tourism. Lastly, the key policy recommendations based on the outcomes of the study are encouraging clean energy investment, enhancing good governance, and sustainable tourism development for improving environmental quality.

     

Identifying impact of international trade and renewable energy consumption on environmental quality improvement and their role in global warming

There is a lack of proper research that highlights the impact of institutional quality (IQ) and renewable energy consumption (REC) on the carbon emission (CE). The significance of IQ and REC in the achievement of zero CE is highlighted in this research. The current research reports the effects of these important factors on the consumption-based carbon emissions in the G-7 countries from 1995 to 2018. Based on the outcome of the cointegration test, the long-run connection is recognized between IQ, REC, GDP, exports, imports, and consumption-based CE. The findings also validated that there exist significant decrease and increase in the CE in both the short and long run; for instance, IQ, REC, and exports decrease the CE, while imports and GDP increase the CE. The estimates of causality test showed that policies aimed at improving IQ, REC, GDP, exports, and imports have a significant impact on the CE. Consequently, based on these results, policymakers in the G-7 must prioritize IQ and REC to enhance environmental quality and attain carbon neutrality.

     

Conditional effect of governance quality on the finance-environment nexus in a multivariate EKC framework: evidence from the method of moments-quantile regression with fixed-effects models

This paper investigates the mitigating effect of governance quality on the finance-environment nexus in a multivariate EKC framework in 123 selected countries during the 1990–2017 period. We mainly employ the method of moments-quantile regression (MM-QR) with the fixed-effects model, among others. First, the MM-QR estimator reveals that financial development reduces environmental quality more significantly in countries with initially higher levels (the 75^th and 90^th quantiles) of CO₂ emissions than in other countries (the 25^th and 10^th quantiles). Second, the attenuating effect of governance quality on the finance-environment nexus is more remarkable in nations with low initial levels (the 25^th and 10^th quantiles) of CO₂ emissions. Third, we find that the marginal positive effect of financial development on CO₂ emissions is smaller under a good regulatory framework than under corruption control and the rule of law, especially in the top emitters (the 75^th and 90^th quantiles). Fourth, unlike oil, which has a considerable negative impact on the environmental quality of the major emitters, renewable energy usage reduces CO₂ emissions in countries in all quantiles, primarily in the lowest quantiles. Fifth, the findings also show that urbanization dramatically worsens environmental quality in all economies, particularly those in the lowest quantiles. Finally, we confirm that the EKC hypothesis holds in all countries across different quantiles. The study’s final section discusses policy implications for sustainable development in all countries.

     

Economic complexity,ICT, biomass energy consumption,and environmental degradation: evidence from Iran

Economic complexity, biomass energy consumption, and information communication technology (ICT) have diverse impacts on energy consumption and carbon dioxide (CO₂) emissions. Nevertheless, analysis of these variable effects is not addressed in the previous literature; the antiqueness of this article is stuffing this gap. This study assessed the relationship between gross domestic product (GDP) per capita, biomass consumption, economic complexity index (ECI), ICT, and CO₂ emissions in Iran in 1994–2018. The autoregressive distributed lag (ARDL) model and the quantile regression (QR) econometric technique were used to investigate the factors affecting CO₂ emissions in the tails of the conditional distribution. The share of each influential factor was predicted through the variance decomposition analysis (VD) for the next 10 years. The empirical results showed a long-run relationship between the variables. So, the variables of biomass consumption, ECI, and ICT improve the quality of the environment in Iran by reducing CO₂ emissions, and the per capita GDP variable increases CO₂ emissions. Results suggest no evidence indicating the presence of environmental Kuznets curve (EKC); however, QR demonstrated the existence of EKCs in the lower quantiles of the conditional distribution. The ECI will have the most share to change the CO₂ emissions in the future. The income threshold should be determined at the turning point of the EKC to increase economic development. Moreover, investing in increasing biomass consumption is vital. Policymakers also need to consider strict added value for the export of products.

     

Does regional energy consumption disparities assist to control environmental degradation in OBOR: an entropy approach

China launched the One Belt & One Road (OBOR) initiative to minimize the energy resource shortage. The China’s nearby countries are rich in energy resources especially Middle East and North Africa (MENA) and Asian countries which make them ideal locations to cooperate with China in terms of energy resources, as 42.8% of world energy consumption belongs to OBOR countries. The present study elaborates the spatial distribution pattern of energy consumption disparities and its impact on environment. To do this, an entropy approach is utilized to compute the energy consumption inequalities in OBOR and its regions. The spatial and Pareto analysis show that MENA, East, and Southeast Asian economies have the highest degree of energy consumption inequalities, while European and Central Asian economies show the lowest energy consumption inequalities in OBOR region. The long-run estimates indicate that energy consumption inequalities enhance the CO₂ emission in OBOR and its region except South and Southeast Asia. Financial development also has a significantly positive impact on CO₂ emission in all models for OBOR and its regions except East Asia. Based on findings, the spatial distribution analysis is applicable to maintain balance in regional energy consumption inequality within OBOR and its regions.

     

The impact of CO2 capture in the power and heat sector on the emission of SO2, NOx,particulate matter,volatile organic compounds and NH3 in the European Union

This study quantifies the trade-offs and synergies between climate and air quality policy objectives for the European power and heat (P&H) sector. An overview is presented of the expected performance data of CO₂ capture systems implemented at P&H plants, and the expected emission of key air pollutants, being: SO₂, NO_X, NH₃, volatile organic compounds (VOCs) and particulate matter (PM). The CO₂ capture systems investigated include: post-combustion, oxyfuel combustion and pre-combustion capture.For all capture systems it was found that SO₂, NO_x and PM emissions are expected to be reduced or remain equal per unit of primary energy input compared to power plants without CO₂ capture. Increase in primary energy input as a result of the energy penalty for CO₂ capture may for some technologies and substances result in a net increase of emissions per kWh output. The emission of ammonia may increase by a factor of up to 45 per unit of primary energy input for post-combustion technologies. No data are available about the emission of VOCs from CO₂ capture technologies.A simple model was developed and applied to analyse the impact of CO₂ capture in the European P&H sector on the emission level of key air pollutants in 2030. Four scenarios were developed: one without CO₂ capture and three with one dominantly implemented CO₂ capture system, varying between: post-combustion, oxyfuel combustion and pre-combustion.The results showed a reduction in GHG emissions for the scenarios with CO₂ capture compared to the baseline scenario between 12% and 20% in the EU 27 region in 2030. NO_x emissions were 15% higher in the P&H sector in a scenario with predominantly post-combustion and lower when oxyfuel combustion (?16%) or pre-combustion (?20%) were implemented on a large scale. Large scale implementation of the post-combustion technology in 2030 may also result in significantly higher, i.e. increase by a factor of 28, NH₃ emissions compared to scenarios with other CO₂ capture options or without capture. SO₂ emissions were very low for all scenarios that include large scale implementation of CO₂ capture in 2030, i.e. a reduction varying between 27% and 41%. Particulate Matter emissions were found to be lower in the scenarios with CO₂ capture. The scenario with implementation of the oxyfuel technology showed the lowest PM emissions followed by the scenario with a significant share allocated to pre-combustion, respectively ?59% and ?31%. The scenario with post-combustion capture resulted in PM emissions varying between 35% reduction and 26% increase.