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.

     

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 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.

     

Does the level of renewable energy matter in the effect of economic growth on environmental pollution? New evidence from PSTR analysis

This study investigates the relationship between environmental pollution and economic growth in the context of renewable energy in OECD countries using the panel smooth transition regression (PSTR) model for 1995–2018. The study finds the value of the threshold variable, calculated as the share of renewable energy use in total energy consumption, to be 7.825%. In this context, economic growth affects the environment negatively and increases environmental pollution when the share of renewable energy use in energy consumption is below the threshold. When this share is above the threshold, it reduces environmental pollution by affecting the environment positively. In addition, the findings reveal a non-linear inverted U-shaped relationship between the environment and economic growth in the context of renewable energy, and the Environmental Kuznets Curve (EKC) hypothesis is valid. Therefore, the widespread use of renewable energy is a solution to reducing environmental pollution. Accordingly, it is very important for policymakers to both highlight and encourage renewable energy use. Furthermore, countries need to both invest in this area and focus on R&D to increase renewable energy production.

     

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.

     

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.

     

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.

     

A new perspective to environmental degradation: the linkages between higher education and CO2 emissions

Although there have been many studies, focusing on basic determinants of carbon dioxide emissions (CO₂), the effect of higher education, which has the potential to be an important determinant of CO₂, has been neglected. The paper aims to display the potential mechanisms between higher education and CO₂ and expand the environmental economics literature. In the paper, the trade-off between higher education and CO₂ is tested by autoregressive distributed lag (ARDL) during the period 1983–2017 in Turkey. Results denote that cointegration exists and an increase in higher education negatively affects CO₂. We also find that economic growth and energy consumption positively affect CO₂ both in the long run and short run. Vector error correction model (VECM) reveals that higher education, economic growth, energy consumption, trade openness, and exchange rates are the causes of CO₂ in the long run. Also, energy consumption and economic growth are the causes of CO₂ in the short run. Therefore, higher education can be used to overcome environmental problems.

     

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.

     

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.

     

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.

     

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.

     

The effects of air pollution on human mortality: does gender difference matter in African countries?

The relationship between environmental factors and human health has long been a concern among academic researchers. We use two indicators of environmental pollution, namely particulate matter (PM₁₀) and carbon dioxide (CO₂) to examine the effects of poor air quality on human mortality. This study explores an issue that has largely been ignored, particularly in the African literature, where the effect of air pollution on human mortality could be influenced by gender specification. We analyse a panel data from 35 African countries and our result suggests that the elevated levels of PM₁₀ and CO₂ have a significant effect on the increasing mortality rates in infants, under-five children and adults. Although the effect of poor air quality on adults is found to differ between genders, such difference is not statistically significant. We conclude that the air pollution effects, on average, are similar between genders in the African countries.     

Improving Urban Air Quality in China: Beijing Case Study

Abstract

China is undergoing rapid urbanization because of unprecedented economic growth. As a result, many cities suffer from air pollution. Two-thirds of China’s cities have not attained the ambient air quality standards applicable to urban residential areas (Grade II). Particulate matter (PM), rather than sulfur dioxide (SO₂), is the major pollutant reflecting the shift from coal burning to mixed source pollution. In 2002, 63.2 and 22.4% of the monitored cities have PM and SO₂ concentrations exceeding the Grade II standard, respectively. Nitrogen oxides (NO_x) concentration kept a relatively stable level near the Grade II standard in the last decade and had an increasing potential in recent years because of the rapid motorization. In general, the air pollutants emission did not increase as quickly as the economic growth and energy consumption, and air quality in Chinese cities has improved to some extent. Beijing, a typical representative of rapidly developing cities, is an example to illustrate the possible options for urban air pollution control. Beijing’s case provides hope that the challenges associated with improving air quality can be met during a period of explosive development and motorization.     

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.

     

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.

     

Combined role of industrialization and urbanization in determining carbon neutrality: empirical story of Pakistan

A rapid process of industrialization, on the one hand, transformed the economies from agrarian to industrial societies to improve the living standards and welfare of people. On the other hand, the urbanized and industrialized economies have posed challenging threats to environmental sustainability. The query at hand is whether the growing environmental emissions are driven by industrialization and urbanization or not. This research aims to empirically examine the combined role of industrialization and urbanization in achieving carbon neutrality in Pakistan by considering foreign direct investment and economic growth as control variables in the model. The core empirical results are the following: firstly, industrialization and economic growth exhibit negative but statistically insignificant impacts on CO₂ emissions, imparting a neutral role in determining the environmental degradation in Pakistan. Secondly, urbanization and foreign direct investment disclose positive and statistically significant (at 1% level of significance) impacts on CO₂ emissions, manifesting an environmental degradation driving impact in the country. Thirdly, given the slope coefficients of urbanization and foreign direct investment (0.058 and 0.035), urbanization proved to be a stronger driver than foreign direct investment. Finally, foreign direct investment is revealed to make the Pakistani economy a “Pollution Haven” for the foreign enterprises in the country. Based on empirical results, none of the variables predicted the support for carbon neutrality in Pakistan.

     

Estimates of carbon dioxide emissions based on incomplete condition information: a case study of liquefied natural gas in China

Recent calculations of carbon dioxide (CO₂) emissions have faced challenges because data consist of only partial information, which is called “incomplete information.” According to the emission factor method, energy consumption and CO₂ emission factors with incomplete information may lead to unmatched multiplication between themselves, which affects accuracy and increases uncertainties in emission results. To address a specific case of incomplete information that has not been fully explored, we studied the effects of incomplete condition information on the estimates of CO₂ emissions from liquefied natural gas (LNG) in China. Based on Chinese LNG sampling data, we obtained the specific-country CO₂ emission factor for LNG in China and calculated the corresponding CO₂ emissions. By applying hypothesis testing, regression analysis, variance analysis, or Monte Carlo (MC) simulations, the effects of incomplete information on the uncertainty of CO₂ emission calculations in three cases were analyzed. The results indicate that calorific values have more than a 9.8% impact on CO₂ emission factors and CO₂ emissions with incomplete sample information. Regarding incomplete statistical information, the impact of statistical temperature on CO₂ emissions exceeds 5.5%. Regarding incomplete sample and statistical information, sample and statistical temperatures can individually increase estimate biases by more than 5.2%. Significantly, the impacts of sample temperature and statistical temperature may offset each other. Therefore, the incomplete condition information is quite important and cannot be ignored in the estimation of CO₂ emissions from LNG and international fair comparison.

     

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.