Assessment of contribution of Australia's energy production to CO2 emissions and environmental degradation using statistical dynamic approach

Linkages between environmental sustainability, disaggregated emission, renewable energy, and energy efficiency: An evidence from BRI countries

This paper examines the long-term and short-run causative relationship among environmental sustainability, energy efficiency, renewable energy and carbon emissions from all over sources (coal, oil and fossil fuels) and sector wise division (heat and power, transportation, residential, manufacturing and other sectors. The empirical evidence presented in this study is derived from a balanced panel dataset spanning the annual periods from 2000 to 2021. The dataset specifically focuses on a selection of BRI Countries. The Kao test demonstrates the presence of cointegration across variables such as carbon dioxide emissions, environmental suitability, energy efficiency and renewable energy. The Panel Pooled Mean Group-Autoregressive Distributed Lag (PMG-ARDL) model indicates a statistically significant positive association between the environmental sustainability and disaggregated CO2 emissions over a long-term period. The study found a positive relationship between disaggregated CO2 emissions and environmental sustainability and energy efficiency, with renewable energy sources reducing emissions. It suggests a need for a structural transition from an energy-intensive economy to a decarbonized one, with sectors like heat and power positively impacting sustainability. Implementing measures to reduce emissions is crucial for tackling climate change.

The road to decarbonization in Australia. A Morlet wavelet approach

The path toward sustainable development is closely related to the intensification of renewable energy sources and the continual innovation of technologies. To evaluate the role of renewable energy consumption and technological innovations on carbon emissions in Australia, this study uses the Morlet wavelet approach. This study identified temporal and frequency variations by applying wavelet correlation, continuous wavelet transforms, and partial and multiple wavelet coherence methods on data from 2000 to 2021. The wavelet correlation revealed that non-renewable energy, globalization, and economic growth are positively correlated with carbon emissions at all scales. In contrast, carbon emissions are negatively correlated with renewable energy and technological innovation at all scales. Meanwhile, the wavelet coherence analysis shows that non-renewable energy contributes to increased CO2 emissions from the short to long term, whereas renewable energy usage negatively affects CO2 emissions across all frequency scales. The study findings indicate that increasing the proportion of renewable energy usage in the total energy mix will curb CO2 emissions over the long run. Accordingly, the way to achieve sustainable development is shifting to a low-carbon economy centered on renewable energy sources, enhancing energy efficiency, and using carbon storage and capture technologies.

An investigation of the nexus between green innovation and environmental sustainability in Vietnam: new evidence from the wavelet analysis

The research investigates the interactions between ecological sustainability and green technologies in Vietnam at different time and frequency dimensions from 1992 to 2019. This study investigates these correlations and their frequency domains by employing innovative multivariate wavelet analysis techniques. The multiple coherencies between green technologies and ecological sustainability suggest one cycle was placed at low frequencies (periodicity of approximately 5-14 years) and spanned from 1996 to 1998. Two significant coexisted cycles at low frequencies were from 2001 to 2004 and 2001 to 2009. The three additional cycles were situated at high frequencies (periodicity of approximately 1-5 years). These cycles ran from 2004 to 2006, 2014 to 2016, and another cycle from 2017 to 2019. The partial wavelet coherency of green technology growth and CO2 emissions suggests that green technology causes alterations in CO2 emissions, and the association is negative from 1996 to 2003 and from 2012 and 2015; both indications are in sync. CO2 emissions pushed from 2004 to 2010, and CO2 emissions pushed anti-phase connectedness from 2016 to 2019. The inconsistency between green technologies and renewable energy use shows that changes in renewable energy consumption are caused by green technology. The relationship is negative from 1996 to 2003, while renewable energy utilization is in step with green technologies pushing from 2011 to 2019. Novel findings in Vietnam in this paper is vital for policymakers to design policies to promote the use of green technologies toward environmental sustainability.

Navigating carbon emissions in G-7 economies: a quantile regression analysis of environmental-economic interplay

This study employs panel data from 1990 to 2020 for the G-7 countries (Canada, France, Germany, Italy, Japan, the UK, and the USA) and employs the examination of heterogeneous slope coefficients and cross-sectional dependence tests as preliminary steps before conducting cointegration analysis and second-generation unit-root tests. This study employs the method of movement quantile regression (MMQR) to analyze long-run and short-run relationships. The findings from the MMQR model indicate that economic growth and imports have a negative impact on consumption-based CO2 (CCO2) emissions, which worsens at higher quantiles. On the other hand, exports, energy efficiency, and renewable energy output (REO) have a positive effect on mitigating CCO2 emissions, with this effect becoming more pronounced at higher quantiles. Furthermore, the robustness of the results was confirmed through rigorous checks using quantile regression with optimized Markov Chain Monte Carlo techniques, which is a reliable non-parametric approach. These checks consistently demonstrated a significant impact on CCO2 emissions, thus validating the findings obtained from MMQR. Based on the outcomes, this study recommends that each G-7 nations should make efforts to regulate their CCO2 emissions by adopting measures that foster ecological equilibrium. Moreover, fostering export-driven sectors, exploring innovative strategies for REO, and improving energy efficiency are crucial measures for effectively tackling CCO2 emissions within the G-7 countries. The study highlights that renewable energy output (REO) and energy efficiency effectively mitigate CCO2 emissions at higher quantiles, suggesting the importance of policy measures supporting their development. Additionally, policies targeting import reduction, export promotion, and carbon pricing mechanisms emerge as strategies to curb emissions and foster sustainable development.

Determinants of environmental quality in India: evidence using the bootstrapped ARDL model with structural breaks

This current study examines the impact of renewable energy consumption, agriculture, and globalization on carbon emissions in India over the period from 1980 to 2018. For long-run estimates, we apply Gregory-Hansen's co-integration test, bootstrap ARDL approaches, fully modified ordinary least squares, and dynamic OLS. The empirical results of long-run estimates indicate that a 1% increase in renewable energy consumption, agriculture, and economic globalization will increase carbon emissions by 0.764%, 1.675%, and 0.517%, respectively. Moreover, this study confirms the detrimental effect of these variables on carbon dioxide emissions. Economic globalization coefficients indicate that the scale effect is valid in India. The 2002 economic crisis slowed down the country's growth rate, which reduced the ecological pollution. Several policy recommendations are derived from the empirical findings.

Does globalization and energy usage influence carbon emissions in South Asia? An empirical revisit of the debate

The 2030 United Nations Sustainable Development Goal (SDG) 13 agenda hinges on attaining a sustainable environment with the need to "take urgent action to combat climate change and its impacts". Hence, this study empirically revisits the debate on the effect of nonrenewable energy and globalization on carbon emissions within the framework of the Kuznets hypothesis using an unbalanced panel data from seven South Asian countries (Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka) covering 1980-2019. The variables of interest are carbon emissions measured in metric tons per capita, energy use measured as kg of oil equivalent per capita, and globalization index. To address five main objectives, we deploy four techniques: panel-corrected standard errors (PCSE), feasible generalized least squares (FGLS), quantile regression (QR), and fully modified ordinary least squares (FMOLS). For the most part, the findings reveal that the (1) inverted U-shaped energy-Kuznets curve holds; (2) U-shaped globalization-Kuznets curve is evident; (3) inverted U-shaped turning points for nonrenewable energy are 496.03 and 640.84, while for globalization are 38.83 and 39.04, respectively; (4) globalization-emission relationship indicates a U-shaped relationship at the median and 75th quantile; and (5) inverted U-shaped energy-Kuznets holds in Pakistan but a U-shaped nexus prevails in Nepal and Sri Lanka; inverted U-shaped globalization-Kuznets holds in Bangladesh and Sri Lanka, but U-shaped nexus is evident in Bhutan, Maldives, and Nepal. Deductively, our results show that South Asia countries (at early stage of development) are faced with the hazardous substance that deteriorates human health. Moreover, the non-linear square term of the nonrenewable energy-emissions relationship is negative, which validates the inverted U-shaped EKC theory. Overall, the effect of energy and globalization on carbon emissions is opposite while the consistency at the 75th quantile result indicates that countries with intense globalization are prone to environmental degradation.

Role of financial development, foreign direct investment inflow, innovation in environmental degradation in Pakistan with dynamic ARDL simulation model

The purpose of this research is to determine the impact of innovation, economic growth, financial development, trade, foreign direct investment (FDI), electricity consumption, and urbanization on the environmental degradations in Pakistan. This study has employed the dynamic autoregressive distributed lag model (ARDL), to investigate the actual change in the independent variables and its impact on the dependent variable through graphs. The findings demonstrate that energy consumption, GDP growth, urbanization, and trade negatively influence the carbon emissions in the short term. On the other hand, the findings indicate that in the long term, only GDP growth and trade had a significantly negative impact on emissions. Urbanization has a positive and considerable impact on the emissions of carbon dioxide in the long run. On the other hand, financial development and foreign direct investment (FDI) help reduce the environmental degradation in the short term and long term. Moreover, innovation positively affects the carbon emissions in both the long and short run. Policy recommendations are given based on the findings of this study.

CO2 emissions-energy consumption-militarisation-growth nexus in South Africa: evidence from novel dynamic ARDL simulations

This study draws ardent attention to the Sustainable Development Goal 13 (climate change mitigation) of the United Nations by investigating the CO₂ emissions-energy consumption-militarisation-economic growth nexus for South Africa (SA) from 1960 to 2019. The researcher applied frequency domain causality and the novel dynamic autoregressive distributed lag (ARDL) simulation approaches to achieve the research objective. The main findings reflected that (i) there is a long-run equilibrium relationship between the variables; (ii) there is no causality between militarisation and energy consumption; (iii) unidirectional causality runs from militarisation to economic growth; (iv) there is no causality between militarisation and CO₂ emissions; and (v) unidirectional causality runs from energy consumption to economic growth. The dynamic ARDL simulations' main results suggest that (i) in the short-run, a positive and insignificant relationship exist between militarisation and CO₂ emissions. Conversely, a negative and significant relationship was recorded in the long-run. Thus, the treadmill theory of destruction is not valid for SA. (ii) In the short-run, economic growth has a positive and significant impact on CO₂ emissions, while in the long-run, economic growth has a negative and significant impact on CO₂ emissions. This implies the environmental Kuznets curve (EKC) hypothesis holds for SA. Overall, this research suggests a synergy between defence, energy, growth, and environmental policies in the short- and long-run to promote and maintain environmental quality in SA.

Consumption of energy from conventional sources a challenge to the green environment: evaluating the role of energy imports, and energy intensity in Australia

Conventional energy consumption such as coal, natural gas, and oil is a source of deteriorating environmental sustainability as well as a severe challenge to the green environment. The present paper explores the nexus between CO₂ emissions, energy imports, energy intensity, and power generation from renewable and non-renewable energies from 1990 to 2021 in Australia. Based on the ARDL model, the findings reveal that energy imports and power generation from non-renewable energy sources show an adverse effect on the green environment. A 1% increase in conventional energy imports leads to an 11% increase in CO₂ emissions. Similarly, a 1% increase in energy generation from conventional sources will increase CO₂ emissions by 45%. On the other hand, lower energy intensity and power generation from renewable sources reveal a positive effect on environmental quality. A 1% increase in energy intensity will decrease CO₂ emissions by 92% while energy generation from non-conventional sources by 15%. Most interestingly, energy intensity reveals the foremost position among all the selected variables to decarbonize and effectively transform conventional energy to clean and green energy production and utilization. The robustness test outcomes confirm the results of the empirical output. Furthermore, this study suggests that governments and policymakers should focus on the adaptation of lower energy intensity for the purpose to reduce CO₂ emissions and promote a clean and green environment. Finally, power generation from renewable energy sources plays an inevitable role which ultimately helps environmentally sustainability in Australia.

Identification of aged-rice adulteration based on near-infrared spectroscopy combined with partial least squares regression and characteristic wavelength variables

The long-term storage of rice will inevitably be involved in the deterioration of edible quality, and aged rice poses a great threat to food safety and human health. The acid value can be employed as a sensitive index for the determination of rice quality and freshness. In this study, near-infrared spectra of three kinds of rice (Chinese Daohuaxiang, southern japonica rice, and late japonica rice) mixed with different proportions of aged rice were collected. The partial least squares regression (PLSR) model with different preprocessing was constructed to identify the aged rice adulteration. Meanwhile, a competitive adaptive reweighted sampling (CARS) algorithm was used to extract the optimization model of characteristic variables. The constructed CARS-PLSR model method could not only reduce greatly the number of characteristic variables required by the spectrum but also improve the identification accuracy of three kinds of aged-rice adulteration. As above, this study proposed a rapid, simple, and accurate detection method for aged-rice adulteration, providing new clues and alternatives for the quality control of commercial rice.

The evolution of the environmental Kuznets curve hypothesis assessment: A literature review under a critical analysis perspective

Environmental changes based on factors like urbanization, population, economic growth, increase in energy consumption, and agricultural intensification are never far from the top of any agenda. The topics of environmental degradation and climate change cannot be confined to a single country or region but need to be addressed on a global scale. If the focus is on the relationship between environmental degradation and economic growth, then one hypothesis that is comprehensively used as an empirically model is the widely known Environmental Kuznets Curve. A substantial amount of research has been published about the Environmental Kuznets Curve, and this present study provides a detailed and extensive literature review of more than 200 articles from 1998 to 2022 to explain and assess its evolution. This literature review provides in detail the Environmental Kuznets Curve relationship under analysis, the additional variables included, the type of analysis and methods performed, the relationships obtained, and if the turning point is calculated. Furthermore, this comprehensive literature points out critical issues and gaps in the Environmental Kuznets Curve analysis. It is important to note that there are components that are not considered in the Environmental Kuznets Curve analysis. The Environmental Kuznets Curve only focuses on production and overlooks the impact of the consumption of imported goods on the environment. Consequently, environmental improvements from technological progress will be offset, and economic growth will result in more environmental degradation. This goes against the change in consumer behaviour which occurs with a rise in income, which is one basic assumption of the Environmental Kuznets Curve. The relocation of pollutant industries and consequent relocation of emissions could distort the emissions trajectory over the economic growth path and is also not considered in the Environmental Kuznets Curve analysis. On the other hand, the growth path traced by the inverted U-shaped is not efficient, and the environmental damage provoked in the first phases of the EKC might not be repairable. Therefore, technological progress, climate finance, and energy transition could improve the Environmental Kuznets Curve assessment.

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A EKC literature survey of more than 200 articles from 1998 to 2022.

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Comprehensive description of the EKC evolution and its functional specification.

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Three dilemmas of the EKC are explained by the Green Solow Model.

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EKC estimation is sensitive to functional specification.

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Climate finance and technological progress could influence EKC assessment.

The relationship between financial development and renewable energy consumption in South Asian countries

We analyse how financial development and renewable energy consumption are linked in the selected countries of South Asia using data covering from 1990 to 2018. On the indication of cross-sectional dependency among the variables of the models, we apply second-generation panel unit root tests and cointegration tests to check stationarity properties and long-run cointegrating relationships. We find that variables are stationary at the first difference, and long-run cointegration exists. By applying robust heterogeneous and cross-section augmented dynamic estimators, we find that growth in GDP increases renewable energy consumption by about 0.50-1.56%; however, it reduces by 0.01-0.03% after particular thresholds. Furthermore, on average, an increase in financial development reduces the propensity of renewable energy consumption by 0.07-0.15% in the long-run. On the other hand, panel causality results show unidirectional relationships from GDP to financial development and from financial development to renewable energy consumption but not vice versa. We suggest that the selected countries revisit and restructure the renewable energy policy and focus on institutional reforms to strengthen renewable energy development in the upcoming years.

The role of liquefied petroleum gas in decarbonizing India: fresh evidence from wavelet-partial wavelet coherence approach

India is predominantly a fossil fuel-intensive South Asian country that has traditionally settled for higher economic gains at the expense of lower environmental quality. However, in the contemporary era, it has become essential for India to come up with viable solutions that can enable the nation to transform its economy into a low-carbon one. Although replacing fossil fuel use with renewable energy sources is assumed to be the ideal pathway to decarbonizing the Indian economy, achieving this clean energy transition involves a long-term process. Thus, the Indian government should rather consider adoption of interim solutions to the environmental pollution problems faced by the nation. Against this backdrop, this study looks at whether enhancing the consumption level of liquefied petroleum gas, a relatively cleaner fossil fuel, can help India reduce its carbon dioxide emissions figures and attain environmentally sustainable economic growth. The econometric analysis is designed as per the theoretical framework of the environmental Kuznets curve hypothesis whereby the effects of economic growth on carbon dioxide emissions are examined controlling for liquefied petroleum gas consumption in the context of India between 1990 and 2018. Based on the findings from the autoregressive distributed lag model bounds test analysis, it is witnessed that there are long-run cointegrating relationships among per capita levels of carbon dioxide emissions, real gross domestic product, and liquefied petroleum gas consumption of India. Besides, the environmental Kuznets curve hypothesis is found to be valid only in the short run; however, it does not sustain in the long run since the economic growth-carbon dioxide emissions nexus is observed to follow a U-shaped relationship in the long run. Moreover, higher liquefied petroleum gas consumption is found to boost carbon dioxide emissions in the short run while reducing it in the long run. Furthermore, the findings from the wavelet and partial wavelet coherence and causality analyses also advocate in favor of promoting the use of liquefied petroleum gas in India in order to significantly curb the energy use-related carbon dioxide emission figures of the nation. Hence, considering these important findings, this study recommends that the Indian government should design policies for augmenting liquefied petroleum gas into the national energy mix and also adopt relevant green economic growth strategies in order to facilitate environmentally-sustainable growth of its economy.

Crude Oil Market Functioning and Sustainable Development Goals: Case of OPEC++-Participating Countries

This article aims to substantiate the factors by which the oil industry influences the sustainable development of OPEC++-participating countries under conditions of uncertainty. The impact of the price parameters of the world oil market and the tools of its regulation on the sustainability of OPEC++-participating countries was assessed using panel regression analysis. The sustainable development level of OPEC++-participating countries was analyzed by the integrated estimation method, focusing on crude oil market functioning features. Undoubtedly, we can testify that there is a direct correlation between the country’s level of socio-economic development and sustainable development. In resource economies, a reduction in oil production and exports cannot have the same effect on sustainable development as in countries that do not produce oil, or are characterized by a higher level of economic development. With an appropriate level of economic diversification and the effectiveness of the institutional framework for managing the oil market, sustainable development can be achieved. Based on the model of the integrated assessment of the sustainable development of oil-exporting countries, the impact of statistically significant financial investors’ panic factor on the imbalance of oil prices due to the uncertainty of economic development was determined. Key indicators that create a panic factor in the oil market were identified. These include the indicators of the number of countries enforcing lockdown and the pandemic’s duration. We argue for the need to develop an effective strategy for achieving the sustainable development goals (SDGs) in OPEC++-participating countries, based on the management of crude oil supply and demand forces and by considering the effect of financial investors’ panic factor on the oil market.

Asymmetric impact of energy utilization and economic development on environmental degradation in Somalia

While there are enormous studies on climate change in stable countries, climate policy perspectives from conflict-prone regions including Somalia are limited. It is noteworthy that environmental degradation is an alarming issue that fuels the vulnerability of Somalia to climate change. To this end, this study investigates the asymmetric impact of energy and economic growth on environmental degradation in Somalia-by employing nonlinear autoregressive distributed lag model (NARDL) and causal techniques from 1985 to 2017. We find asymmetric long-term cointegration among the variables, whereas energy consumption and economic growth asymmetrically affect environmental degradation. Besides, the causal inferences reveal unidirectional causality from environmental pollution to positive change in energy consumption. Additionally, a bidirectional causality is observed between population growth and negative change in economic growth. A unidirectional causality is confirmed: from positive shock in economic growth to population growth-from a negative change in economic growth to negative shock in energy consumption-from positive change in economic growth to positive shock in energy consumption-and from a negative change in energy consumption to population growth. This calls for the implementation of clean energy investment and modern environmental strategies including good farming methods and improved grazing land policies. The adoption of these policies will improve both environmental quality and sustained economic development.

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.

Analysis of Agricultural CO2 Emissions in Henan Province, China, Based on EKC and Decoupling

Global warming caused by greenhouse gas emissions is highly concerning. Both the environmental Kuznets curve (EKC) hypothesis and decoupling analysis indicate a dynamic relationship between economic growth and environmental pollution, and each method has its own emphasis. The objective of this paper is to investigate the nexus between grain production and agricultural carbon emissions for the main grain-producing areas in China. Taking Henan Province, the second largest agricultural province, as an example, this paper examines the relationship between grain production and agricultural CO2 emissions during 2000–2019, using the EKC hypothesis and decoupling analysis. The results are as follows: (1) The estimation model of CO2 EKC shows the climbing stage of an inverted U-shaped relationship, which suggests that agricultural economic growth occurred at the cost of an increase in agricultural CO2 emissions in Henan Province during the past 20 years. (2) The results of the decoupling analysis show that incidences of weak decoupling and expansive coupling states took up most of the study period, accompanied by an occasionally strong decoupling state; decoupling and coupling states alternated irregularly, and no clear development trends were observed. (3) Considering the shape of the CO2 EKC and the decoupling state, environmental policies encouraged decoupling, but suffered from time lags and poor continuity; long-term incentives, such as an ecological compensation policy, could perhaps drive carbon emission reduction. On this basis, Chinese agricultural policy should combine environmentally targeted interventions with measures supporting production and farmers’ incomes, and environmental policy should also adapt to economic growth. Only when both supplement each other can sustainable agricultural goals be achieved.

Exploring the asymmetric effects of renewable energy production, natural resources, and economic progress on CO2 emissions: fresh evidence from Pakistan

A bulk of literature has examined the asymmetric impact of renewable energy consumption on CO₂ emissions by using the advanced econometric approach. While the asymmetric role of renewable energy production in the CO₂ equation is largely unknown, our present study quantifies the asymmetric relationship between renewable energy production, natural resources, economic progress, and CO₂ emission for Pakistan by using the NARDL approach. It is found that positive change in renewable energy production has a positive effect on CO₂ emissions, while a negative change in renewable energy production has a negative effect on CO₂ emissions in the long run. Furthermore, a positive and negative change in natural resources contributes negatively to CO₂ emissions in the long run. The results reveal that a positive change in economic progress significantly increases CO₂ emissions in the long run. Based on findings, Pakistan's government should encourage local and international investors to increase their investment in the production of renewable energy by reducing environmental degradation.

Time-frequency dependency of temperature and sea level: a global perspective

The importance of environmental sustainability to all human aspects has been spiking as the world keeps evolving. Economies around the world are on the move to ensure sustainable economic development and a clean atmosphere through the use of renewable energy sources. Since the end of the nineteenth century, it is recognized that a global mean sea level rise speed about 1.7 ± 0.2 mm/year, but the rate has increased to 3.2 ± 0.4 mm/year. In this study, we investigated the dynamic linkage between average temperature and sea level within the global framework covering 1881 to 2013. The paper employs wavelet analysis to investigate the short-term and long-run causal links between global average temperature anomalies and global sea level. In this respect, our findings indicate that (i) a significant vulnerability in global average temperature and sea level is observed over the selected study period; (ii) global average temperature has considerable power for predicting sea level, particularly in the long-term. The causality test revealed a bi-directional causal relationship between global average temperature and sea level and unidirectional flow from global average temperature to sea level. And the study confirms the "conservation hypothesis," and it has long-run implications for environmental quality. Thus, minimizing global average temperature anomalies is a decisive ingredient for minimizing sea level rise. Based on these outcomes, both developed and developing countries' policymakers should support the Paris agreement (COP21) agreement to control CO₂ emissions growth. Policymakers should encourage the usage of environmentally friendly energy sources that will enhance environmental quality and hold the increase in global average temperature below 1.5 °C.

The Contribution of Outward Foreign Direct Investment, Human Well-Being, and Technology toward a Sustainable Environment

This study evaluates the impact of outward foreign direct investment (OFDI), human well-being, and other macro indicators of the public sector on carbon footprint. Empirical analysis has been carried out for newly industrialized economies that span the period 1990–2017. We used augmented mean group and bootstrap panel causality techniques to cogitate the cross-sectional dependence and country-specific heterogeneity. Based on cross-country analysis, study results show that growing OFDI reduces carbon footprint efficiently in Mexico and Turkey, human well-being decreases emissions in the Philippines, and urbanization reduces emissions in China. Further, technology reduces emissions in Malaysia and Turkey, trade openness reduces emissions in China and Malaysia, and natural resource rents reduce emissions in Indonesia and Mexico. In the case of panel analysis, the moderating role of OFDI with human well-being is contributing toward a sustainable environment. Moreover, the moderation of OFDI and urbanization has an insignificant impact on CFP. Findings depict that interaction terms of OFDI with technology and trade openness have a positive association with the environment quality. Finally, OFDI and natural resources have positive moderation on CFP. This study contributes to the existing literature by suggesting policy implications for a sustainable environment.

An asymmetric analysis of the impacts of energy use on carbon dioxide emissions in the G7 countries

The foremost theme of the paper is to explore the asymmetric/symmetric impact of energy consumption on the carbon dioxide emission of G7 countries (Germany, Canada, USA, Italy, France, Italy, UK, and Japan). The nonlinear autoregressive distributed lag is used to measure asymmetric/symmetric cointegration by using annual data of G7 countries from 1965 to 2019. The augmented Dickey-Fuller and structural break unit root test is employed to measure the stationarity in variables while the Brock, Dechert, and Scheinkman test is used for measuring nonlinearity and the Wald test is used to figure out short- and long-run asymmetries/symmetries, respectively. The estimated findings of the nonlinear autoregressive distribution lag model show a significant effect of energy use on the ecological footprint. The asymmetric causality test provides evidence of unidirectional, bidirectional, and asymmetrical/symmetrical causality among the variables of G7 nations. The finding of the study suggested policy for the government of Canada and France to use coal instead of oil and gas while the USA, Germany, Italy, UK, and Japan are required to consume gas as compared to oil and coal. Similarly, the study also suggests using modern technology, renewable energy, and preventive measurement for ensuring environmental betterment.

Dynamic Effect of Oil Resources on Environmental Quality: Testing the Environmental Kuznets Curve Hypothesis for Selected African Countries

This paper examines the environmental Kuznets curve (EKC) theory, augmenting the role of oil resources and energy consumption in carbon dioxide (CO2) emissions using the annual data of 11 African oil-producing countries from 1980 to 2014. We apply advanced panel cointegration and panel autoregressive distributive lag (ARDL) techniques coupled with Granger non-causality analysis to account for cross-sectional dependence and heterogeneity. The results of the augmented mean group (AMG) reveal that oil resources abundance degrades the environmental quality in Angola while abating CO2 emissions in Algeria, Gabon, Morocco, and Nigeria. Contrarily, energy consumption escalates pollution in the Congo Democratic Republic (COD), Côte d’Ivoire (CIV), Gabon, Morocco, and Tunisia. Our findings support the EKC hypothesis only in Cameroon, CIV, and Nigeria while exhibiting a U-shaped curve in Algeria and Morocco. Causality analysis unveils that oil resources Granger cause energy consumption, suggesting the balance between renewable and non-renewable energy sources. The current study has important policy implications for promoting green technology, economic diversification, service sector, and green investments.

The impact of macroeconomic and financial development on carbon dioxide emissions in Pakistan: evidence with a novel dynamic simulated ARDL approach

This paper has empirically explored the impact of macroeconomic and financial development on CO₂ emissions by utilizing a novel dynamic simulated ARDL model for annual time series data from 1982 to 2018 for Pakistan. The results of a novel dynamic simulated ARDL disclosed that the growth of stock market, FDI, economic growth, and consumption of oil wield a positive impact on CO₂ emission, while domestic credit exerts a negative effect on CO₂ emission both in the short and the long run in Pakistan. The stock market development and domestic credit wield a significant influence on carbon dioxide emission in Pakistan both in the long and the short run. FDI exerts significant impact only in the long run, while economic growth and consumption of oil wield significant impact only in the short run on CO₂ emission in Pakistan. This study opens up new visions for the economy of Pakistan to sustain financial and economic growth by protecting environment from pollution through its efficient national environmental policy, fiscal policy, and monetary policy.

Decarbonization of Australia’s Energy System: Integrated Modeling of the Transformation of Electricity, Transportation, and Industrial Sectors

To achieve the Paris Agreement’s long-term temperature goal, current energy systems must be transformed. Australia represents an interesting case for energy system transformation modeling: with a power system dominated by fossil fuels and, specifically, with a heavy coal component, there is at the same time a vast potential for expansion and use of renewables. We used the multi-sectoral Australian Energy Modeling System (AUSeMOSYS) to perform an integrated analysis of implications for the electricity, transport, and selected industry sectors to the mid-century. The state-level resolution allows representation of regional discrepancies in renewable supply and the quantification of inter-regional grid extensions necessary for the physical integration of variable renewables. We investigated the impacts of different CO2 budgets and selected key factors on energy system transformation. Results indicate that coal-fired generation has to be phased out completely by 2030 and a fully renewable electricity supply achieved in the 2030s according to the cost-optimal pathway implied by the 1.5 °C Paris Agreement-compatible carbon budget. Wind and solar PV can play a dominant role in decarbonizing Australia’s energy system with continuous growth of demand due to the strong electrification of linked energy sectors.

The relationship between good governance and CO2 emissions in oil- and non-oil-producing countries: a dynamic panel study of sub-Saharan Africa

This study empirically examined the relationship between CO₂ emissions and good governance in oil- and non-oil-producing countries in the SSA region. The findings from this paper revealed very interesting results proving that good governance has a negative relationship with CO₂ emissions. Oil-producing countries have good governance system to help control and reduce CO₂ emissions as compared to non-oil-producing countries. Particularly, in oil-producing countries, business regulatory environment, budget and fiscal management, as well as fiscal policy have a significant negative relationship with CO₂ emissions. But there is rather a positive relationship between these indicators and CO₂ emissions in non-oil-producing countries as they do not have the required structures and arrangements to control CO₂ emissions. Also, in oil-producing countries, property rights and rules have positive relationship with CO₂ emissions but in the case of non-oil-producing countries, there is a negative relationship, meaning that non-oil-producing countries have good legal system and rule-based governance structures that is capable of protecting property rights. There is positive relationship between quality of government administration and CO₂ emissions in oil-producing countries but negative for non-oil-producing countries. Trade liberalization and economic growth have positive relationship with CO₂ emissions in both categories. But urbanization has a negative relationship with CO₂ emissions in non-oil-producing countries but positive for oil-producing. The findings point that effective and efficient institutions is a vital element for SSA countries to help combat the increased emissions of CO₂ to engender growth.

How does fossil energy abundance affect China's economic growth and CO2 emissions?

The paper uses the nonparametric additive regression model with data- driven characteristics to investigate the impact of fossil energy abundance on China's economic growth and carbon dioxide (CO₂) emissions. The results show that the effect of fossil energy abundance on economic growth shows an inverted "U-shaped" pattern in the eastern region, due to the changes in coal mining, oil processing, and coking investments. On the contrary, fossil energy abundance exerts a positive "U-shaped" nonlinear effect on economic growth in the central region. This indicates that in the early stages fossil energy abundance did not play a role in promoting economic growth, and its driving effect was only prominent in the later stages. In addition, fossil energy abundance generates a positive "U-shaped" impact on CO₂ emissions in the eastern and central regions, because of the changes in coal and oil consumption at different stages. However, fossil energy abundance has an inverted "U-shaped" nonlinear effect on CO₂ emissions in the western region, on account of the phase difference in the production and consumption of natural gas and oil.

Renewable energy, urbanization, and ecological footprint in the Middle East and North Africa region

The countries in the Middle East and North Africa (MENA) region have the greatest potential for renewable energy consumption in the world and is likely to be the most vulnerable to the horrendous effects of climate change. Unfortunately, only a few of the countries have tapped into this potential, as non-renewable energy still dominates the total energy mix of these countries. This study explores the effect of renewable and non-renewable energy consumption on the environment in MENA countries from 1990 to 2016 by applying the Augmented Mean Group algorithm while accounting for urbanization, financial development, and economic growth. The panel result suggests that financial development, economic growth, and urbanization add to environmental degradation. Also, findings reveal that renewable energy does not contribute meaningfully to environmental quality, while non-renewable energy consumption significantly adds to environmental degradation. A uni-directional causality flows from urbanization, economic growth, and energy use to environmental degradation. One way to abate this damage is for countries in this region to embrace and promote the consumption of clean energy sources.

An assessment of environmental sustainability corridor: The role of economic expansion and research and development in EU countries

Given that the European Union-28 countries proposed a target of 3% of the Gross Domestic Product on research and development (R&D) expenditure by 2020, the current study attempts to examine the role of R&D on environmental sustainability. In addition, the study further investigates the long-run and causal interaction between, renewable energy consumption, nonrenewable energy consumption, and economic growth in an ecological footprint-income function. Notably, the study incorporates research and development (R&D) expenditure to the model as an additional variable, and measures impact of each variable on ecological footprint. Empirical evidence is based on a balanced panel data between annual periods of 1997-2014 for selected EU-16 countries. The Pedroni, Johansen Multivariate and Kao tests all reveal a cointegration between ecological footprint, economic growth, research and development expenditure, renewable, and nonrenewable energy consumption. The Fully Modified and Dynamic Ordinary Least Squares models (FMOLS and DOLS) both suggest a negative significant relationship between the countries' research and development expenditure and ecological footprint in the long-run. This implies that spending on R&D significantly impacts on environmental sustainability of the panel countries. Our study affirms that nonrenewable energy consumption and economic growth increase carbon emission flaring while renewable energy consumption declines ecological footprint. The panel causality analysis reveals a feedback mechanism between ecological footprint, R&D expenditure, renewable, and nonrenewable energy consumption. We further observed a one-way causality between ecological footprint and economic growth. The current further validates that the Environmental Kuznet Curve Hypothesis (EKC) holds for this panel of EU countries examined. Effective policy implications could be drawn toward modern and environmentally friendly energy sources, especially in attaining the Sustainable Development Goals via spending on R&D.

How do environmental technologies affect green growth? Evidence from BRICS economies

Green growth has become one of the best alternative strategies for sustainable development. Although environmental technologies play a fundamental role in green growth, further investigations are required to understand whether and how environmental technologies affect green growth. Therefore, this study explores the role of environmental technologies in green growth by controlling renewable and non-renewable energy consumption for BRICS countries. To this end, the study conducts advanced panel data estimation techniques that produce robust results against endogeneity, heteroskedasticity, and cross-sectional dependence issues. Empirical results show that environmental-related technologies positively contribute to green growth. Results also confirm that renewable energy promotes green growth, but non-renewable energy is detrimental to green growth. BRICS countries need to improve innovations in the energy sector for achieving green growth and sustainability targets.

Testing the role of oil production in the environmental Kuznets curve of oil producing countries: New insights from Method of Moments Quantile Regression

The global economic growth has triggered the continual increase in oil demand for transportation and petrochemical sectors which offshoots environmental pollution. Though there exists literature on environmental Kuznets curve, however, very few examine the scope in the light of fossil fuel energy production. This paper investigated the dynamic effect of oil production on carbon emissions in 15 oil-producing countries by accounting for the role of electricity production, economic growth, democracy, and trade over the period 1980-2010. Using the novel Method of Moments Quantile Regression (MMQR) with fixed effects, the results found an inverted U-shape relationship between economic growth and CO₂ emissions only at median and higher emission countries, thus, validating the environmental Kuznets curve hypothesis. Oil production increases CO₂ emissions significantly from the first to sixth quantiles with greater effect at the lowest quantile and weaker effect at the highest quantile. Electricity production was found to increase CO₂ emissions while trade condenses CO₂ emissions across all the quantiles thereby confirming the pollution halo hypothesis for oil-producing countries. The effect of democracy was positive across all the quantiles but only significant in countries with average CO₂ emissions. The findings provide insight for policymakers to mitigate CO₂ emissions in oil-producing countries through diversification and clean energy technologies such as carbon capture and storage.

Fiscal policy and CO2 emissions from heterogeneous fuel sources in Thailand: Evidence from multiple structural breaks cointegration test

This study investigated the dynamic linkage between fiscal policy, energy and CO₂ emissions from heterogeneous fossil fuel sources in the context of the environmental Kuznets curve (EKC) framework for Thailand. With annual data from 1972 to 2014 while incorporating structural breaks, the study employed a Maki cointegration test and the dynamic ordinary least squares estimation approach. The results found that a 1% increase in fiscal policy brought about a 6.5% (p < 0.05) increase in the low CO₂ emitting gaseous fuel sources (natural gas), a 0.2% (p < 0.01) reduction in the intermediate CO₂ emitting liquid fuel sources (crude oil derivatives), and an insignificant increase 0.2% (p > 0.05) in the high CO₂ emitting solid fuel sources (coal derivatives). While a 1% increase in fiscal policy abates aggregated CO₂ emissions by 0.2% (p < 0.05), the existence of the EKC hypothesis was validated in all models. The causality test revealed a bi-directional causal relationship between fiscal policy and CO₂ emissions and unidirectional flow from fiscal policy to energy consumption. This confirms that fiscal policy initiatives towards energy consumption have long-run implications for environmental quality. Our findings support the energy-led growth hypothesis for the Thai economy. The implication of the finding is that increasing the share of clean and renewable energy sources should be encouraged-rather than energy conservation policies, which obstruct energy supply and utilization. This highlights a more efficient way of harnessing energy sources through the instrumentality of fiscal policy.

Dynamic impact of trade policy, economic growth, fertility rate, renewable and non-renewable energy consumption on ecological footprint in Europe

Climate change mitigation has become the central theme for many policy initiatives, as such, the European Union (EU) member countries are working assiduously to achieve the emission targets. To provide policy direction in achieving the emission targets, this study investigated the drivers essential to attaining the Sustainable Development Goals in regards to reducing environmental pollution in EU member countries. A balanced panel of 16-EU countries from 1997 to 2014 was estimated with Panel Pool Mean Group Autoregressive distributive lag (PMG-ARDL) model. The study traced the equilibrium relationship between ecological footprint, real gross domestic product, trade openness, fertility rate, renewable and non-renewable energy consumption - suggested by both Kao and Pedroni cointegration tests. The PMG-ARDL analysis confirmed the role of non-renewable energy consumption in depleting environmental quality while renewable energy consumption was found to improve environmental sustainability. Interestingly, the unexpected long-run fertility-ecological footprint nexus was connected with the divergent fertility rate information of the EU member countries. Although, country-specific policy approach is essential, however, such a framework should be compatible with the region's overall Sustainable Development Goals. The call for diversification of existing energy portfolios by either incorporating or enhancing renewable energy technologies is essential to sustain the current success strides of most member states. Thus, the EU needs to strengthen its commitments to achieving the emission targets by decarbonizing and sustaining its economic growth trajectory.

Proximate determinants of particulate matter (PM2.5) emission, mortality and life expectancy in Europe, Central Asia, Australia, Canada and the US

BACKGROUND

The growing concern with environmental related impacts on mortality and morbidity means that the conceptual framework of environment-health-economic policy nexus is salient in the global debate on air pollution.

OBJECTIVES

With time series data spanning 2000-2016, this study explored the proximate determinants of ambient air pollution, mortality, and life expectancy in North America, Europe & Central Asia, and East Asia & Pacific regions.

METHODS

The study applied historical data on urban population, total pollution, energy consumption, GDP per capita, life expectancy, mortality rate and industrial PM_2.5 emissions to develop six parsimonious models using the generalized least squares (GLS) random-effects model estimation with first-order autoregressive [AR(1)] disturbance across 54 countries.

RESULTS

An increase in income level by 1% declined mortality rate by 0.01% and increased longevity by ~0.02% (95% Confidence Interval [CI]) in the long-run. An increase in industrial PM_2.5 emissions per capita by 1% decreased life expectancy by 0.004% and mortality rate by 0.02% (95% CI). Intensification of energy consumption and its related services by 1% were found to increase industrial PM_2.5 emissions by 0.42-0.45% (95% CI). An inversed-U shaped curve between PM_2.5 emissions per capita and income levels was found at a turning point of US$ 48,061. The validity of an environmental Kuznets curve hypothesis between ambient air pollution and urbanization was confirmed, while a rapid increase in population had a significant positive impact on ambient air pollution.

CONCLUSION

Ambient air pollution contributes significantly in reducing life expectancy and increasing mortality. However, sustained economic development, along with energy efficiency, and sustainable urban settlement planning and management are potential options for reducing ambient air pollution while improving quality of life and environmental sustainability.

Revealing long- and short-run empirical interactions among foreign direct investment, renewable power generation, and CO2 emissions in China

This work systematically examines the empirical interactions among foreign direct investment (FDI), renewable power generation (RPG), hydropower generation (HPG), non-hydropower generation (NHPG), and CO₂ emissions in the long run and short run. To test the existence of long-run equilibrium association among those variables, Bayer-Hanck combined cointegration and autoregressive distributed lag (ARDL) model have been employed on time series of China for the period 1991-2017. The vector error correction model-based short-run impacts among the variables of interest are also estimated. Besides, Toda-Yamamoto causality and Granger causality are employed to confirm the direction of causal links. The existence of a long-run equilibrium relationship is revealed in case of all types of specification. The expansion of both FDI and CO₂ emissions boosted RPG, HPG, and NHPG in the short run and long run, with greater intensity of impacts in the long run. To reflect comparisons, it is found that the renewables generation driving the impact of CO₂ emissions and FDI on NHPG is greater than RPG, which further exceeds HPG. In turn, the RPG, HPG, and NHPG mitigated CO₂ emissions both in the long run and short run, with stronger impacts in the long run. Moreover, the CO₂ emissions inhibition impact of HPG dominated NHPG, which further exceeded that of RPG. The FDI boosted CO₂ emissions in a way that the long-run pollution haven impact is revealed to be powerful than that of the short run. A unidirectional causality has been observed running from FDI to CO₂ emissions, RPG, HPG, and NHPG. A bidirectional causality is found operative between CO₂ emissions and RPG/HPG/NHPG. Interestingly, the long-run and short-run impacts remained homogeneous in terms of directionality. Nevertheless, strict heterogeneity is observed in terms of the degree of impacts. Based on empirics, both long-term and short-term policies on FDI, renewables generation, and CO₂ emissions are vital for decision-makers in China. Graphical abstract.

Do agricultural activities induce carbon emissions? The BRICS experience

This study investigates the environmental Kuznets curve (EKC) hypothesis for Brazil, Russia, India, China and South Africa (BRICS) over the period 1990-2014, while considering agricultural activities, energy use, trade openness and mobile use as driving forces of environmental degradation. The empirical results verify an inverted U-shaped connection between carbon emissions and economic growth. This study confirms the unfriendly impact of agriculture on the environment. Electricity consumption and trade openness likewise exhibit similar impacts on carbon emissions. Mobile use however reduces pollution. A unique revelation from this study is that the interaction between electricity consumption and agricultural activities has an additional pernicious effect on the environment. The methodologies applied for testing the impact of selected independent variables on carbon emissions in BRICS are the Dynamic Ordinary Least Squares (DOLS) and the Fully Modify Ordinary Least Square (FMOLS) for long run regression. Empirical evidence confirms that agriculture exerts a negative impact on the environment in BRICS countries. This study therefore recommends the adoption of cleaner energy processes and enabling high-tech and clean foreign investment.

Effect of energy consumption and economic growth on carbon dioxide emissions in Pakistan with dynamic ARDL simulations approach

Environmental degradations are mainly caused by the use of different energy resources for economic growth. This research examined the influence of energy consumption (coal consumption, oil consumption, and gas consumption) and economic growth on environmental degradation in Pakistan. This research used newly developed method dynamic ARDL simulations to scrutinize the actual influence of positive and negative change in the use of coal consumption, oil consumption, and gas consumption for energy and economic growth on environmental degradation in Pakistan. The examined results of dynamic ARDL indicate that economic growth, coal consumption, oil consumption, and natural gas consumption have positive impact on the environmental degradations in Pakistan both in short run and long run. It is suggested that environmental degradations can be reduced by promoting renewable energy sources for energy.

Renewable energy in Southeast Asia: Policies and recommendations

Southeast Asian countries stand at a crossroads concerning their shared energy future and heavily rely on fossil fuels for transport and electricity. Within Asia, especially India and China lead the world renewable energy generation undergoing a period of energy transition and economic transformation. Southeast Asian countries have huge potentials for sustainable energy sources. However they are yet to perform globally in renewable energy deployment due to various challenges. The primary objective of the study is to examine the renewable energy growth and analyse the government policies to scale up the deployment of renewables for power generation substantially. The study also offers policy recommendations to accelerate renewable energy exploitation sustainably across the region. To achieve the ambitious target of 23% renewables in the primary energy mix by 2025, ASEAN Governments should take proactive measures like removal of subsidies of fossil fuels, regional market integration and rapid implementation of the existing project. Eventually, each of this strategy will necessitate sustained leadership, political determination, and concrete actions from stakeholders, in particular, increased cooperation across the region.

Environmental sustainability assessment using dynamic Autoregressive-Distributed Lag simulations-Nexus between greenhouse gas emissions, biomass energy, food and economic growth

Increasing population demand has triggered the enhancement of food production, energy consumption and economic development, however, its impact on climate change has become a global concern. This study applied a novel environmental sustainability assessment tool using dynamic Autoregressive-Distributed Lag (ARDL) simulations for model estimation of the relationships between greenhouse gas (GHG) emissions, energy, biomass, food and economic growth for Australia using data spanning from 1970 to 2017. The study found an inversed-U shaped relationship between energy consumption and income level, showing a decarbonized and services economy, hence, improved energy efficiency. While energy consumption increases emissions by 0.4 to 2.8%, biomass consumption supports Australia's transition to a decarbonized economy by reducing GHG emissions by 0.13% and shifts the demand for fossil fuel. Food and energy consumption underpin socio-economic development and vice versa. However, food waste from production and consumption increases ecological footprint, implying a lost opportunity to improve food security and reduce environmental pressure from agricultural production. There is no single path to achieving environmental sustainability, nonetheless, the integrated approach applied in this study reveals conceptual tools which are applicable for decision making.

Comparative study on the influence of final use structure on carbon emissions in the Beijing-Tianjin-Hebei region

The Beijing-Tianjin-Hebei region's rapid economic development has led to a dramatic increase in its CO₂ emissions, which is closely related to various regions' consumption habits and structures. In this paper, the decomposition analysis method based on input and output (IO-SDA) was applied to decompose the CO₂ emissions change of the Beijing-Tianjin-Hebei region from 1997 to 2012 into five driving factors: population, carbon emission efficiency, production structure, final use structure and per capita regional GDP, and then the final use structure factor was further analyzed. The results show that: (1) the population and per capita regional GDP promote the CO₂ emissions of all regions; Carbon emission efficiency is the biggest offsetting factor; The effect of final use structure changes on the growth of CO₂ emissions in Beijing and Hebei remains unchanged. The effect on Tianjin was from 0.7Mt offset to 0.8Mt promotion. (2) Urban household consumption is the most important factor offsetting CO₂ emissions in Beijing. Investment and export are the most important final use types for promoting the growth of CO₂ emissions in Tianjin and Hebei, with the contribution of 95.78% and 88.09%, respectively. (3) From the sectoral perspective: The construction sector has the greatest impact on the total capital formation of the three regions. In terms of exports, Beijing's tertiary industry has the largest offsetting effect, while Tianjin and Hebei mainly rely on the promotion of metal smelting and other manufacturing industries. Finally, some policy implications for low carbonization are proposed in the Beijing-Tianjin-Hebei region.

Improving the environmental impact of palm kernel shell through maximizing its production of hydrogen and syngas using advanced artificial intelligence

Fossil fuel depletion and the environmental concerns have been under discussion for energy production for many years and finding new and renewable energy sources became a must. Biomass is considered as a net zero CO₂ energy source. Gasification of biomass for H₂ and syngas production is an attractive process. The main target of this research is to improve the production of hydrogen and syngas from palm kernel shell (PKS) steam gasification through defining the optimal operating parameters' using a modern optimization algorithm. To predict the gaseous outputs, two PKS models were built using fuzzy logic based on the experimental data sets. A radial movement optimizer (RMO) was applied to determine the system's optimal operating parameters. During the optimization process, the decision variables were represented by four different operating parameters. These parameters include; temperature, particle size, CaO/biomass ratio and coal bottom ash (CBA) with their operating ranges of (650-750 °C), (0.5-1 mm), (0.5-2) and wt% (0.02-0.10), respectively. The individual and interactive effects of different combinations were investigated on the production of H₂ and syngas yield. The optimized results were compared with experimental data and results obtained from Response Surface Methodology (RSM) reported in literature. The obtained optimal values of the operating parameters through RMO were found 722 °C, 0.92 mm, 1.72 and 0.06 wt% for the temperature, particle size, CaO/biomass ratio and coal bottom ash, respectively. The results showed that syngas production was significantly improved as it reached 65.44 vol% which was better than that obtained in earlier studies.

Outlook of carbon capture technology and challenges

The greenhouse gases emissions produced by industry and power plants are the cause of climate change. An effective approach for limiting the impact of such emissions is adopting modern Carbon Capture and Storage (CCS) technology that can capture more than 90% of carbon dioxide (CO₂) generated from power plants. This paper presents an evaluation of state-of-the-art technologies used in the capturing CO₂. The main capturing strategies including post-combustion, pre-combustion, and oxy - combustion are reviewed and compared. Various challenges associated with storing and transporting the CO₂ from one location to the other are also presented. Furthermore, recent advancements of CCS technology are discussed to highlight the latest progress made by the research community in developing affordable carbon capture and storage systems. Finally, the future prospects and sustainability aspects of CCS technology as well as policies developed by different countries concerning such technology are presented.

Toward a sustainable environment: Nexus between CO2 emissions, resource rent, renewable and nonrenewable energy in 16-EU countries

The study investigates the long-run and causal interaction between, renewable energy consumption, nonrenewable energy consumption, and economic growth in a carbon function. The current study incorporates natural resources rent to the model as an additional variable. Empirical evidence is based on a balanced panel data between annual periods of 1996-2014 for selected EU-16 countries. The Kao test reveals a cointegration between carbon dioxide emissions, economic growth, natural resources rent, renewable, and nonrenewable energy consumption. The Panel Pooled Mean Group-Autoregressive Auto regressive distributive lag model (PMG-ARDL) suggests a positive significant relationship between the countries' natural resource rent and CO₂ emissions in the long-run. Implying that the overdependence on natural resource rent affects environmental sustainability of the panel countries if conservation and management options are ignored. Our study affirms that nonrenewable energy consumption and economic growth increase carbon emission flaring while renewable energy consumption declines CO₂ emissions. The panel causality analysis reveals a feedback mechanism between economic growth, renewable, and nonrenewable energy consumption. We further observed a feedback causality between natural resources rent and economic growth. Effective policy implications could be drawn toward modern and environmentally friendly energy sources, especially in attaining the Sustainable Development Goals.

What drives environmental degradation? Evidence from 14 Sub-Saharan African countries

Although Sub-Saharan Africa (SSA) countries make less environmental pollution compared with other regions, the notably increasing economic growth and accelerating process of urbanization have resulted in the increase of energy needs and, thus, lead to environmental degradation. To empirically investigate the determinants of environmental degradation by accounting for the significant roles played by economic growth, non-renewable and renewable energy consumption, and urbanization, a balanced panel dataset of 14 SSA countries over 1990-2014 is utilized. Also, the ecological footprint (EF), considered a more comprehensive indicator, is used as a proxy of environmental degradation. The results confirm strong cross-sectional dependence within the SSA countries. The Augmented Mean Group (AMG) estimator indicates that economic growth, non-renewable energy consumption, and urbanization exert positive effects on the EF in the SSA countries, while renewable energy consumption plays a negative role in the EF. Moreover, bidirectional long-run causality runs among economic growth, non-renewable consumption, urbanization, and the EF; in contrast, unidirectional causality is found to run from renewable energy consumption to the EF. Therefore, for the SSA countries, the upgrading of industrial structure and further improvement of renewable energy are needed. In addition, urbanization plays a crucial role in contributing to environmental degradation and requires immediate policy response in the SSA countries.

Another look at the relationship between energy consumption, carbon dioxide emissions, and economic growth in South Africa

This study explores the energy use and economic growth nexus from 1960 to 2016 in South Africa while accounting for capital, labour, and carbon dioxide emissions. We applied Bayer and Hanck (2013) combined co-integration approach, Pesaran et al. (2001) bounds test and Kripfganz and Schneider (2018) critical values and approximate p-values. The empirical evidence finds support for a long-run equilibrium relationship among investigated variables. The Granger causality test indicates one-way causality from energy use to economic growth, validating the energy-led growth hypothesis. Our study found an inverted U-shaped pattern between energy use and economic growth in the long run. This finding suggests that at a higher level of economic development there is less intensification of energy consumption, hence, signifying a decline in energy intensity while validating energy efficiency in South Africa.

What are the main factors affecting carbon price in Emission Trading Scheme? A case study in China

Emission Trading Scheme (ETS) has the potential to influence energy consumption, environmental quality and economy directly and ETS price is the key of ETS market. On December 27, 2017, China's carbon trading market was officially launched, which may be the largest platform of ETS in the world. Therefore, this paper seeks to assess the influencing factors of emission trading price (industry coverage, the annual decline factor, and free allowance rate) and analyzes the impact mechanism in detail by applying computable general equilibrium model. The results show that ETS price and emission reduction have a significant positive correlation; key factors can impact the price significantly. Fewer industries, higher annual decline factor, and higher free allowance rate will push ETS price up. The paper also found that ETS prices are unpredictable when the mechanism is not yet fully determined. It further, argues that ETS prices are unpredictable when the mechanism is not yet fully determined because of the high relationship between ETS price and the mechanism of ETS. These findings will assist policymakers to build a healthy ETS market. The important implication is that we can adjust the market price by adjusting these mechanisms.

Multi-Scenario Analysis of Energy Consumption and Carbon Emissions: The Case of Hebei Province in China

In view of the complexity of the energy system and its complex relationship with socio-economic factors, this study adopts the Long-range Energy Alternative Planning (LEAP) model, a technology-based, bottom-up approach, scenario-based analysis, to develop a systematic analysis of the current and future energy consumption, supply and associated Green House Gas (GHG) emissions from 2015 to 2050. The impact of various energy policies on the energy system in Hebei Province was analysed by considering four scenarios: a Reference Scenario (REF), Industrial Structure Optimization Scenario (ISO), Terminal Consumption Structure Optimization Scenario (TOS) and Low-carbon Development Scenario (LCD). By designing strategic policies from the perspective of industrial adjustment, aggressive energy structure policies and measures, such as the ISO and the TOS, and even more aggressive options, such as the LCD, where the percentage of cleaner alternative energy sources has been further increased, it has been indicated that energy consumption will have increased from 321.618 million tonnes of coal equivalent (Mtce) in 2015 to 784.88 Mtce in 2050 in the REF, with a corresponding increase in GHG emissions from 920.56 million metric tonnes (Mt) to 2262.81 Mt. In contrast, the more aggressive policies and strategies involved in the LCD, which combines the ISO with the policy-oriented TOS, can lower energy consumption by 50.82% and CO2 emissions by 64.26%. The results shed light on whether and how these scenarios can shape the energy-carbon emission reduction trajectories and develop the low-carbon pathways in Hebei Province.

Does energy consumption follow asymmetric behavior? An assessment of Ghana's energy sector dynamics

The study answered the following questions: First, does energy evolves in different regimes by transitioning over a finite set of unobserved states? Second, does energy consumption follow an asymmetric behavior over "energy boom" and energy scarcity? and, Third, are there unobserved factors underpinning energy crisis? We employed Markov-switching dynamic regression to examine the asymmetric effect, NIPALS regression to examine energy determinants and neural network analysis for prediction. The neural network model suggests a 99% prediction of energy consumption by the predictor variables. It was evident that energy consumption evolves in two states by transitioning over a finite set of unobserved states. The 11.6% growth in energy consumption is expected to occur in 4.1 years while energy crisis is expected to last for 3.7 years. Technological advancement and the development of green energy through foreign direct investment are essential to improve energy sector portfolio.

A review on Environmental Kuznets Curve hypothesis using bibliometric and meta-analysis

The Environmental Kuznets Curve (EKC) hypothesis dates back in decades and is still topical presently due to its importance in environmental policy formulation. There are several systematic reviews of the EKC hypothesis using traditional review method. However, this review employs bibliometric and meta-analysis to track historical trends on the theme using the VOSviewer software and meta-analytic methods. The review translates the network analysis into visualized forms based on authors' contribution, the impact of the research by countries, citations count, and text corpus modeling using a network data extracted from Web of Science. The meta-analysis reveals that the collection of studies that validate the inversed-U shaped relationship has an average of US$8910 as the turning point of annual income level. Low income and middle-income countries are found below the thresholds of annual income level while high-income countries are above. Heterogeneity is confirmed among turning point in studies on EKC hypothesis due to differences in the period of study and econometric methods used in model estimation. The empirical findings reveal that most of the studies on EKC hypothesis are based on atmospheric indicators, while literature is sporadic and limited on EKC hypothesis which employs land indicators, oceans, seas, coasts and biodiversity indicators, and freshwater indicators.

Effect of foreign direct investments, economic development and energy consumption on greenhouse gas emissions in developing countries

In accordance with the Sustainable Development Goal 17 of improving global partnership for sustainable development, this study examined the effect of foreign direct investment inflows, economic development, and energy consumption on greenhouse gas emissions from 1982 to 2016 for the top five emitters of greenhouse gas emissions from fuel combustion in the developing countries, namely; China, India, Iran, Indonesia and South Africa. The study employed a panel data regression with Driscoll-Kraay standard errors, U test estimation approach and panel quantile regression with non-additive fixed-effects. The study found a strong positive effect of energy consumption on greenhouse gas emissions and confirmed the validity of the pollution haven hypothesis. The environmental Kuznets curve hypothesis is valid for China and Indonesia at a turning point of US$ 6014 and US$ 2999; second, a U-shape relationship is valid for India and South Africa at a turning point of US$ 1476 and US$ 7573. Foreign direct investment inflows with clean technological transfer and improvement in labour and environmental management practices will help developing countries to achieve the sustainable development goals. Mitigation of greenhouse gas emissions depends on enhanced energy efficiency, adoption of clean and modern energy technologies, such as renewable energy, nuclear, and the utilization of carbon capture and storage for fossil fuel and biomass energy generation processes.