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.

     

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.

     

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.

     

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.

     

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.

     

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.

     

Nexus among electricity consumption,foreign direct investment and aggregate economic activity towards Nigeria’s economic performance: evidence from a trivariate causality model

It is evident that there is nexus among electricity consumption, foreign direct investment and aggregate economic activity. Unfortunately, the causal relationship among the three variables in Nigeria based on modern econometric methods, recent time-series data and ways that sufficiently cater for inflation and population growth has not been adequately investigated. This study, among other things, used a trivariate vector error correction model, autoregressive distributed lag bounds test for cointegration and Granger causality test to analyse the causal relationship among electricity consumption, foreign direct investment and aggregate economic activity based on time-series data from 1970 to 2018. The study found the presence of neutral causality between electricity consumption and aggregate economic activity in the short run as well as unidirectional causality from aggregate economic activity to electricity consumption in the long run. The study also found the presence of unidirectional causality from foreign direct investment to electricity consumption as well as neutral causality between foreign direct investment and aggregate economic activity in both the short run and the long run. It is therefore recommended that steps should be taken to adequately increase foreign direct investment and aggregate economic activity in ways that will guarantee an optimal increase in electricity consumption in Nigeria.

     

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.

     

Environmental quality vs economic growth in a developing economy: complements or conflicts

An increase in economic activities which leads to economic growth has been adduced as a possible factor for environmental degradation. While some other studies have argued that as economies keep growing, there are possibilities for resource redistribution which could engender environmental balance, thus engendering the argument on the conflicting-complementary position of the environment-growth nexus. In the light of this, this study uses previous activities between economic activities and the environment to determine the conflicting or complementary relationship that exists between economic growth and the environment. Also, using Nigeria as a case study, the design of environmental growth nexus to achieving sustainable development is assessed. Annual time series data between 1970 and 2014 were sourced from the World Development Indicators. Following the neoclassical perspective on ecological growth and the Kuznets inverted U-hypothesis on the environment-growth relations, stationarity test was performed, and the autoregressive distributed lag estimates were employed. From the study, it is seen that factors like rainfall that promotes environmental quality in the long run promote economic growth (per capita and GDP growth) in Nigeria. Similarly, factors like natural resource utilization, which depletes environmental quality, increases economic growth but reduces economic growth per capita; thus, with questions for development, the possibility of a complementary relationship for environmental quality and economic growth is spotted if the right policies are ensured. Also, the study found evidence of a growing conflicting relation between environmental quality (CO₂) and economic growth (per capita and GDP growth). Meanwhile, these conflicts to a great extent find expression in the Kuznets hypothesis; such that, if policies that promote income per capita reduces pollution and pursues eco-efficiency via economic growth are properly harnessed, there are the prospects of meeting up with the goals of environmental sustainability in developing economies.

     

Evaluating pollution damage function through carbon pricing,renewable energy demand,and cleaner technologies in China: blue versus green economy

Climate change and increased greenhouse gas emissions boost the global average temperature to less than 2°C, which is the estimated breakeven point. The globe is moving into blue pollution economies as the environmental sustainability objective becomes more distorted. The study looked at three United Nations Sustainable Development Goals, namely (i) affordable and clean energy; (ii) industry, innovation, and infrastructure; and (iii) climate change, to see how far the Chinese economy has progressed toward green and clean development strategy. In the context of China, the “pollution damage function” was intended to refer to carbon damages related to carbon pricing, technological variables, sustained economic growth, incoming foreign investment, and green energy. The data was collected between 1975 and 2019 and analyzed using various statistical approaches. The results of the autoregressive distributed lag model suggest that carbon taxes on industrial emissions reduce carbon damages in the short and long run. Furthermore, a rise in inbound foreign investment and renewable energy demand reduces carbon damages in the short term, proving the “pollution halo” and “green energy” hypotheses; nonetheless, the results are insufficient to explain the stated results in the long run. In the long run, technology transfers and continued economic growth are beneficial in reducing carbon damages and confirming the potential of cleaner solutions in pollution mitigation. The causal inferences show the one-way relationship running from carbon pricing and technology transfer to carbon damages, and green energy to high-technology exports in a country. The impulse response estimates suggested that carbon tax, inbound foreign investment, and technology transfers likely decrease carbon damages for the next 10 years. On the other hand, continued economic growth and inadequate green energy sources are likely to increase carbon pollution in a country. The variance decomposition analysis suggested that carbon pricing and information and communication technology exports would likely significantly influence carbon damages over time. To keep the earth’s temperature within the set threshold, the true motivation to shift from a blue to a green economy required strict environmental legislation, the use of green energy sources, and the export of cleaner technologies.

Graphical abstract

Source: Authors’ self-extract

     

Energy and emission benefits of chicken manure biogas production: a case study

Studies on the production of biogas of different organic materials in an anaerobic environment are being carried out all over the world. The most important parameters in these researches can be listed as raw material potential, production processes, economic analyses, and environmental effects. Chicken manure is one of the raw materials used in biogas production. In this study, in addition to the analysis of biogas and energy production potential from chicken manure, greenhouse gas emissions were analyzed to evaluate environmental effects. In Turkey, chicken manure is not adequately processed and causes environmental pollution. The model biogas plant and potential energy generation were researched in this field study. The pilot plant produces 8.58 million m³ of biogas per year by processing about 110 thousand tons of waste. It produces 17 GWh/year of electricity and 16 GWh/year of thermal energy, as well as reducing CO₂ greenhouse gas emissions by 13.86 thousand tons/year.

     

The role of green innovations,environmental policies and carbon taxes in achieving the sustainable development goals of carbon neutrality

The green innovations, environmental policies, and carbon taxes are the tools to achieve sustainable development goals (SDGs) in the mitigation process. This study is intended to examine the impact of innovation, carbon pricing (CTAX), environmental policies (EP), and energy consumption (ECON) on PM_2.5 and greenhouse gas (GHG) emission for Central-Eastern European countries. The panel effect during 2000–2018 is tested using a dynamic panel data model while the Granger causality approach obtains country-related outcomes. The outcomes reveal that eco-friendly innovations have a more profound effect on carbon mitigation. Environmental policies reduce emissions by 2.7% in the short run and 17.4% in the long run. Similarly, CTAX mitigates GHG emissions by 8.6% in the short-run and PM2.5 by 0.9% and 5.7% in the short and long run. However, urbanization, energy consumption and trade openness are the leading polluters in the region. The main findings remain dominant in the country-specific results and find unidirectional and bidirectional causality evidence among variables. The research concludes that green innovations and strict environmental policy can lead towards achieving sustainable development goals using carbon taxes as a tool on the way.

Graphical abstract

     

Could China’s long-term low-carbon energy transformation achieve the double dividend effect for the economy and environment?

Exploring the low-carbon energy transformation pathway is vital to coordinate economic growth and environmental improvement for achieving China’s carbon peak target. Three energy-target scenarios are developed in this paper, considering the targets of energy structure, electrification rate, and carbon mitigation towards 2030 announced by the Chinese government. A dynamic multi-sectoral computable general equilibrium model, CHINAGEM, is employed to examine the economic and environmental effects under different pathways of long-term low-carbon transformation. It detects that China’s energy structure would substantially transfer to the low-carbon and clean one, whereas CO₂, SO₂, and NO_X emissions in 2020–2030 would vastly abate along with all three energy-target scenarios. Different pathways would produce varying positive impacts on China’s macro-economy and achieve the different extent of double dividend effects. It is highly conceivable for China to peak its carbon emission at 12.4 GtCO₂ by 2028 if it serves the comparatively more stringent low-carbon transformation pathways.

     

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.     

Roadmap for climate alliance economies to vision 2030: retrospect and lessons

The United Nations Climate Conference 25, held in December 2019, reached a significant agreement against implementing the Paris agreement come 2020. Bound by the contract, 189 countries who are party to the deal agreed to constrain worldwide temperature to ascend to 1.5° Celsius. To this end, the present study attempts to investigate the readiness of selected countries in the European Union to implement the agreement, which will better the quality of the global environment. In line with this, this study appraises the connection between economic growth, renewable and non-renewable energy consumption, on emissions in 11 countries in the European Union from 1990 to 2016. The study utilises the Pooled Mean Group-Auto Regressive Distributed Lag (PMG-ARDL) model estimator and Dumitrescu and Hurlin Panel Causality analysis to analyse the long-run and short-run impact and direction of causality among these factors, respectively. The long-run study's empirical results show a U-shaped Environmental Kuznets Curve (EKC) and a negative connection between renewable energy use and emissions in the EU-11 countries. In the short-run, non-renewable energy use worsens CO₂ emissions while renewable energy use leads to a fall in emissions. Similarly, causality tests show a feedback mechanism between emissions and renewable energy use and between non-renewable energy and renewable use. Also, there is unidirectional causality from income to CO₂ emissions, non-renewable energy use to CO₂ emissions. The investigation recommends an expanded proportion of renewable energy sources in the EU countries’ energy mix to cut down on emissions.

     

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.

     

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.

     

The role of innovations and renewable energy consumption in reducing environmental degradation in OECD countries: an investigation for Innovation Claudia Curve

Rising economic growth in recent ages is the primary concern of most of the countries to enhance the living standard, but the ever-increasing production of economic activities consumes a lot of energy, which leads to a sharp increase in carbon dioxide emissions. Innovation may be a remedy that can help improve energy efficiency, obtain renewable energy, and promote economic growth, thereby protecting the quality of the environment. Therefore, this paper examines the role of innovation and renewable energy consumption in CO2 reduction in OECD countries from 2004 to 2019. By using the two-step system generalized of moment estimator, the results show that economic growth and innovation significantly increase carbon emissions, however the innovation Claudia Curve (ICC) is verified, and the environmental Kuznets curve does not exist. Foreign direct investment has a negative impact on carbon emissions, thus verifying the Pollution Hao hypothesis, whereas renewable energy also improves environmental quality, but the interaction between innovation and renewable energy consumption still increases carbon emissions. Financial development, industrialization, trade, and energy consumption have also been found to be harmful factors of environmental quality. Our findings have considerable policy implications for OECD countries on the improvement of innovation indicators and investment in renewable energy sources to rise environmental quality.

     

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.

     

Evaluating China’s regional energy and environmental efficiency by considering three internal parallel industries

With the rapid development of China’s economy, high energy consumption and high pollution emission have become serious problems. To solve these problems, many studies have been done to evaluate energy and environmental efficiency, as the results can provide valuable information to improve performance. However, the previous research mainly evaluates China’s regional energy and environmental efficiency by considering each region’s industry as a whole system, ignoring the internal structure. In reality, each region mainly includes three parallel types of industry: primary, secondary, and tertiary. Therefore, this paper provides a parallel data envelopment analysis (DEA) approach to evaluate China’s regional energy and environment efficiency by considering these parallel industrial systems. The following findings can be obtained based on the empirical results: (1) the overall energy efficiency of China is low, and the inefficiency of the economic system is mainly sourced from the lower energy and environmental performance of the primary industry and the tertiary industry. (2) the introduction of the environmental variable (CO₂) leads to the increase of some backward areas’ efficiencies. (3) the energy efficiency of each provincial region is different, and most of them have their own inefficient industries. (4) the total factor productivity of China is declining, mainly because of the decline of technical efficiency.