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Non-fossil fuels are receiving increasing attention within the context of addressing global climate challenges. Based on a review of non-fossil fuel consumption in major countries worldwide from 1985 to 2015, the purpose of this paper is to analyze trends for global non-fossil fuel consumption, share of fuel consumption and inequality.

The similarities were obtained between the logarithmic mean divisia index and the mean-rate-of-change index decomposition analysis methods, and a method was proposed for complete decomposition of the incremental Gini coefficient.

Empirical analysis showed that: global non-fossil fuel consumption accounts for a small share of the total energy consumption, but presents an increasing trend; the level of global non-fossil fuel consumption inequality is high but has gradually declined, which is mainly attributed to the concentration effect; inequality in global non-fossil fuel consumption is mainly due to the difference between nuclear power and hydropower consumption, but the contributions of nuclear power and hydropower to per capita non-fossil fuel consumption are declining; and population has the greatest influence on global non-fossil fuel consumption during the sampling period.

The main contribution of this study is its analysis of global non-fossil fuel consumption trends, disparities and driving factors. In addition, a general formula for complete index decomposition is proposed and the incremental Gini coefficient is wholly decomposed.

In this paper, the authors investigate that the increasing level of fossil fuel combustion in the industrial sector has been considered the prime cause for the emissions of greenhouse gas. Meanwhile, the research focusing on the impact of fossil fuel consumption on the emission of CO₂ is limited for the developing countries containing Vietnam. This study applied the autoregressive distributed lag (ARDL) approach with structural breaks presence, and the Bayer–Hanck combined cointegration method to observe the rationality of the environmental Kuznets curve (EKC) hypothesis in the dynamic relationship between the industrialization and carbon dioxide (CO₂) emission in Vietnam, capturing the role of foreign direct investment (FDI) inflows and the fossil fuel consumption over the period of 1975–2019. The outcomes revealed the confirmation of cointegration among the variables and both short and long-run regression parameters indicated the evidence for the presence of a U-shaped association between the level of industrial growth and CO₂ emission that is further confirmed by employing the Lind and Mehlum U-test for robustness purpose. The results of Granger causality discovered a unidirectional causality from FDI and fossil fuel consumption to CO₂ emission in the short run. For the policy points, this study suggests the use of efficient and low carbon-emitting technologies.

In order to test for consistency and robustness of the cointegration analysis, this study also applied the ARDL bound testing method to find out long-run association among variables with the existence of the structural break in the dataset. The ARDL method was preferred to other traditional cointegration models; because of the smaller dataset, the results obtained from the ARDL method are efficient and consistent and equally appropriate for I(1) and I(0) variables.

The short-run and long-run causal associations among variables have been observed by employing the error correction term (ECT) augmented Granger-causality test that revealed the presence of the long-run causality among variables only when the CO₂ emission is employed as a dependent variable. The outcomes for short-run causality indicated the presence of unidirectional causality between consumption of fossil fuel and CO₂ emission, where the fossil fuel consumptions Granger-cause CO₂ emission. Industrial growth has also been found to have an impact on fossil fuel consumptions, however not the opposite. This advocates that the policies aimed at reducing the fossil fuel consumptions would not be harmful to industrial growth as other energy efficient and cleaner technology could be implemented by the firms to substitute the fossil fuel usage.

The study explored the dynamic relationship among FDI, consumption of fossil fuel, industrial growth and the CO₂ emission in Vietnam for the time period 1975–2019. The newly established Bayer–Hanck joint cointegration method and the ARDL bound testing were employed by taking into account the structural breaks in the dataset.

This study aims to develop a price policy for fossil fuel consumption, as it is an effective instrument to manage the demand-side of energy economics.

This research estimates the demand elasticities of diesel, gasoline, fuel oil and kerosene by using static, dynamic and error-correction models in log-linear form.

The findings show that fossil fuel demand responds to price changes less than income changes, as fuel price is inelastic, but income is elastic. In that respect, the impact of price change decreases constantly with increasing energy price, followed by subsidy reform. Subsidy removal and price policy reformation is the UN recommendation for subsidizing countries, including Iran, to reduce fossil fuel consumption, whose intensity depends on the price elasticities.

As a result of this price policy, diesel, gasoline and liquefied petroleum gas prices should increase at least 1.8%–7.3%, 4.4%–6.4% and 7%–8.6%, respectively, and gradually within 2018–2030. The price policy improves all the pillars of sustainable development, including economy, environment and social (health). Overall, such a target can potentially save 3%–29% of diesel, 34%–56% of gasoline and 15%–20% of liquefied petroleum gas, as well as reduce 15%–40% of CO₂ emissions annually, and can save potentially more than 510,000 lives annually. Thus, the energy price policy can fundamentally improve sustainability.

The estimated elasticities outline the required prices to decrease the fossil fuels, according to the UN mitigation targets, as price policy recommendation.

In the backdrop of growing global concern on escalating CO₂ emission leading to climate disorder and controversy between economic growth and environment, this study undertakes a decomposition analysis of the top 20 emitters of the world during 1992–2016 with two objectives: to identify the relative contribution of the major driving factors in CO₂ emission and to comprehend the role and performance of sectoral energy consumption pattern in changing the emission level.

The paper uses variance analysis method to perform two stage decomposition: first, it decomposes emission into the major driving factors, and, secondly, it also decomposes fossil fuel intensity of different sectors into fuel mix and energy intensity effects, which are new in the literature.

The results indicate that aggressive pursuit for economic growth, particularly by developing countries, is the major reason behind unprecedented emission growth, with income effect, fossil fuel intensity effect and population effect having substantial roles. Considerable decline in dependence on fossil fuel, coupled with rising emissions, signifies that emission intensity is still to be harnessed. Sectoral decomposition shows that while fossil fuel intensity has declined in residential sector, it has remarkably shot up in industry, transport and commercial sectors. On the other hand, sectoral energy intensity has declined, particularly due to favourable performances of transport and commercial sectors.

The detailed country-wise sectoral analysis identifies the sectors with favourable contribution in curtailing emission and lends a direction to other countries for policy making.

This study contributes by incorporating multi-country sectoral segregation in decomposition analysis. It focuses not only on energy intensity, but on the effect of energy substitution in each sector as well. It identifies the sectors that have lowered their dependence on fossil fuel to highlight that emission can effectively be dealt with through a prudent choice of fuel mix.

The purpose of this study is to assess the influence of institutional quality (IQ), fossil fuel efficiency, structural change and renewable energy (RE) consumption on carbon efficiency.

This research uses an econometric approach, more specifically the Autoregressive Distributed Lag model, to examine the relationship between structural change, RE consumption, IQ, fossil fuel efficiency and carbon efficiency in India from 1996 to 2019.

This study finds the positive contributions of variables like fossil fuel efficiency, technological advancement, structural transformation, IQ and increased RE consumption in fostering environmental development through enhanced carbon efficiency. Conversely, this study emphasises the negative contribution of trade openness on carbon efficiency. These findings provide concise insights into the dynamics of factors impacting carbon efficiency in India.

This study's exclusive focus on India limits the generalizability of findings. Future studies should include a broader range of variables impacting various nations' carbon efficiency. Furthermore, it is worth noting that this study examines renewable and fossil fuel efficiency aggregated. Future research endeavours could yield more specific policy insights by conducting analyses at a disaggregated level, considering individual energy sources such as wind, solar, coal and oil. Understanding how the efficiency of each energy source influences carbon efficiency could lead to more targeted and practical policy recommendations.

To the best of the authors’ knowledge, this study addresses a significant gap in the existing literature by being the first empirical investigation into the effects of IQ, fossil fuel efficiency, structural change and RE consumption on carbon efficiency. Unlike prior research, the authors consider a comprehensive IQ index, providing a more holistic perspective. The use of a comprehensive composite index for IQ, coupled with the focus on fossil fuel efficiency and structural change, distinguishes this study from previous research, contributing valuable insights into the intricate dynamics shaping India's path towards enhanced carbon efficiency, an area relatively underexplored in the existing literature.

The purpose of this paper is to examine the dynamic linkages amongst ecological footprints, fossil fuel consumption, real income, globalization and population in Egypt in the period from 1971 to 2014.

The paper uses fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) methods to investigate the long run relationships amongst ecological footprints, economic growth, globalization, fossil fuel energy consumption and population. Moreover, the Toda–Yamamoto approach is conducted to examine the causal relationships between variables.

Empirical results of FMOLS and DOLS methods show that real income and fossil fuel consumption are responsible for deteriorating the environment, while globalization and population are found to mitigate it. As for Toda–Yamamoto–Granger causal relationship results, unidirectional causal relation from globalization, population and fossil fuel energy consumption to the ecological footprint exists. Moreover, bidirectional causal relation between real income on the one hand and globalization and the ecological footprint on the other hand is found.

Using carbon dioxide emissions has major weakness as carbon dioxide emissions are considered only part of the total environmental deterioration so this study is the first study for Egypt that uses the ecological footprint as an indicator for environmental quality and environmental pollution and links it with globalization, economic growth, population and fossil fuel energy consumption. Moreover, realizing the direction of causality between these variables might help policymakers in designing the policies to promote the shift towards clean energy sources, especially that achieving sustainable economic growth with more contribution to the global economy depending on diversification of energy sources without deteriorating the environment is considered one of the most important objectives of Egypt’s National Vision 2030.

This study aims to examine the effects of energy transition on pollution emissions in Africa. In addition, it explores the indirect channels through which energy consumption impacts environmental quality.

The study uses system Generalised Method of Moments approach for a panel of 51 developing African countries over the 1996–2020 period.

The results show that fossil fuel and renewable energy consumption increase pollution emissions. The environment-degrading effect of renewable energy in Africa is however counter-intuitive, though the results are robust across regional economic blocks and income groups except for upper-middle-income countries where energy consumption is environment enhancing. Moreover, the results show that the environmental impacts of non-renewable energy consumption are modulated through financial development and information and communication technology (ICT) adoption, leading to respective positive net effects of 0.04460796 and 0.07682873. This is up to respective policy thresholds of 203.265 and 137.105 of financial development and ICT adoption, respectively, when the positive net effects are nullified.

Contingent on the results, the study suggests the need for African countries to develop sound financial systems and encourage the use of green technologies, to ensure that energy transition effectively contributes to emissions reduction. Policymakers in Africa should also be aware of the critical levels of financial development and ICT, beyond which complementary policies are required for non-renewable energy consumption to maintain a negative impact on environmental degradation.

Firstly, extant studies on the nexus between energy transition and environmental degradation in Africa are very sparse. Therefore, this study fills the existing research gap by comprehensively examining the effects of energy transition on pollution emissions across 51 African economies. Additionally, besides accounting for the direct environmental effects of energy transition, the current study accounts for the indirect channels through which the environmental impacts of energy transition are modulated. Hence, this study provides critical thresholds for the policy modulating variables, which enlighten policymakers on the necessity of designing complementary policies once the modulating variables attain the established thresholds.

Energy security has been talked about by governments and policymakers because the global energy market is unstable and greenhouse gas emissions threaten the long-term health of the global environment. One of the most potent ways to cut CO₂ emissions is through the production and consumption of renewable energy. Thus, the purpose of this paper is to highlight the drivers that, if ambitious environmental policies are implemented, might improve energy security or prevent its deterioration.

The study uses a balanced panel data set for Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam that covers a period of 30 years (1990–2020). The pooled panel dynamic least squares is used in this study.

The findings show that renewable energy consumption is positively related to gross domestic product per capita, energy intensity per capita and renewable energy installed capacity. Wherein renewable energy use is inversely related to per capita electricity consumption, CO₂ emissions and the use of fossil fuel electricity.

There is a lack of research identifying the factors influencing energy security in the ASEAN region. Therefore, this study focuses on the drivers that influence energy security, which are explained by the proportion of renewable energy in final energy consumption. Without identifying the demand and supply sources of energy, especially electricity production based on renewable energy techniques, it is hard for policymakers to achieve the desired renewable energy-based outcome.

Australia is one of the ten largest emitters of greenhouse gases but stands out from the others due to its economic growth without recession for 26 consecutive years. This paper aims to focus on the energy-growth nexus and the effects of energy consumption on the environment in Australia.

This analysis is performed using annual data from 1965 to 2015 and the autoregressive distributed lag model.

The paper finds empirical evidence of a trade-off between economic growth and carbon dioxide (CO₂) intensity. The results show that increased gross domestic product (GDP) in Australia increased investment in renewable energy sources (RESs), although the renewable technology is limited and has no impact on reducing CO₂ intensity in the long run. In contrast to investment in RES, fossil fuels, coal and oil, are decreased by GDP. However, oil consumption increased renewable energy consumption, and this reflects the pervading effect of the growing economy.

Overall, this paper contributes to the literature by analysing the behaviour of both energy consumption and the environment on the growing Australian economy. In addition, this paper goes further by studying the impact of economic growth on renewable and non-renewable energy consumption, as well as on CO₂ emissions. The study is conducted on a single country for which literature is scarce, using a recent approach and a long time period.

Consumption of fossil fuels due to their non-renewability has always been one of the fundamental problems among energy-related issues. Major dependence of mining equipment and activities on energy, fuel and adequate fuel allocation has become of great importance in fuel consumption of mines. Therefore, this study aims to propose a model for optimal fuel allocation for mining industry.

In this study, partial least squares structural equation modeling (PLS-SEM), as one of the well-known statistical methods, is used to model and analyze fuel consumption pattern in mine industry.

To show the applicability of the proposed model, the study investigates the model for a real mine in Iran. In this regard, real data of important factors affecting mine fuel consumption are collected. Results of statistical models construct a general formula to calculate the fuel consumption based on three main variables.

Policymaking is one of the important tasks in energy-related organizations. One of the main sectors that uses noticeable amount of fossil fuels is mining industry. Despite the government subsidy for mining in Iran, there is a significant price difference between the price of allocated fuel for mine and the price of the same fuel in the open market. Therefore, this study implements PLS-SEM approach to formulate the fuel consumption pattern under all possible fuel consumption indicators to enable policymakers to make reliable decision for future purposes.