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This study aims to investigate the impact of total primary energy consumption and CO₂ emissions on the economic development in 16 emerging countries.

The panel model was used taking the period 1980-2008.

The results showed that a long-run relationship is present between total primary energy consumption, CO₂ emission, and economic development in the countries under investigation. It was also found that both total primary energy consumption have a positive causal relationship with the economic development and other economic aspects playing an important role in achieving high economic performance with the consequence of higher pollution.

The main recommendation of this study is to increase their investment and government spending on green energy projects to increase the share of green energy out of their total energy consumption. This can be considered a good solution for their energy woes.

Different from the previous studies, it was also found that total primary energy consumption have a positive causal relationship with the economic development and other economic aspects playing an important role in achieving high economic performance with the consequence of higher pollution. In addition, there are a number of countries that had not investigated before.

The purpose of this paper is to attempt to analyze the situation and trend of China's energy consumption structure and predict it.

Starting from the situation of China's energy consumption structure, a quadratic programming model is created to analyze the trend of it. A homogeneous Markov chain is chosen to predict China's energy consumption structure with the data collected from China's Statistical Yearbook. Finally, the implication of the prediction is explained.

The results are convincing: the substitution of different energies are found, China will not enter the oil era, natural gas and non‐fossil energy will rapidly develop.

The results of this article can provide an important basis for the government to make a non‐fossil energy development plan and energy policies.

The paper succeeds in revealing and predicting China's energy consumption structure by quadratic programming and homogeneous Markov chain.

The paper aims to study the relationship between economic growth, nuclear energy consumption and carbon dioxide (CO₂) emissions for a panel of 25 countries over a period of 1993-2010. Through this study, the author has provided an insight into one of the available sources of energy, i.e. nuclear energy and its impact on economic growth and CO₂ emissions.

Separate panels are created for developing and developed economies. Short- and long-run causalities between the variables are established using error correction mechanism.

For the developed countries, short-run causality running from CO₂ emissions to economic growth was estimated, whereas strong form of causality indicated the dependence of CO₂ emissions on economic growth and nuclear energy consumption was seen to impact CO₂ emissions. For the developing countries, both the short-run and strong-form causality estimates indicate that economic growth causes CO₂ emissions.

On policy front, developing countries can safely adopt CO₂ cut-back policies as they are not found to impact economic growth. For the developed countries, such policies may impede growth in the short run, but in the long run these policies do not affect the economic growth.

Keeping in mind the significance of nuclear energy consumption in economic growth and less/no GHG emissions generated by nuclear energy, this study validates its significance. This study, to the best of the author's knowledge, considers the largest panel (i.e. 25 countries) to date and the only study that focuses on studying three different panels (complete dataset, developed countries, developing countries) in one study and applies the vector error correction mechanism to study the causal relationship between nuclear energy consumption, CO₂ emissions and economic growth.

This study is intended to analyze the impact of information and communication technology (ICT) infrastructure, technological innovation, renewable energy consumption and financial development on carbon dioxide emissions in emerging economies.

The present study adopts the autoregressive distributed lag (ARDL) cointegration technique for the annual data collection of Vietnam from 1990 to 2020.

The results of the study unveil that renewable energy consumption, the interaction between renewable energy consumption and ICT infrastructure and financial development have significant predictive power for carbon dioxide emissions. In the long term, renewable energy consumption, export and population growth reduce CO2 emissions, whereas the interaction between renewable energy consumption and ICT infrastructure and financial development increases CO2 emissions, while ICT infrastructure does not affect emissions. In the short run, changes in ICT infrastructure contribute to carbon dioxide emissions in Vietnam. In addition, changes in renewable energy consumption, financial development, the interaction between ICT infrastructure and renewable energy consumption and population growth have a significant effect on CO2 emissions. Notably, technological innovation has no impact on CO2 emissions in both the short and long run.

The current study provides new insights into the environmental effects of ICT infrastructure, technological innovation, renewable energy consumption and financial development. The interaction between renewable energy consumption and ICT infrastructure has a significant effect on carbon dioxide emissions. The paper suggests important implications for setting long-run policies to boost the effects of financial development, renewable energy consumption and ICT infrastructure on environmental quality in emerging countries like Vietnam in the coming time.

The Gulf Cooperation Council (GCC) of countries has some of the highest electricity consumptions and carbon dioxide emissions per capita in the world. This poses a direct challenge to the GCC government’s ability to meet their CO₂ reduction targets. In this review paper the current household electricity consumption situation in the GCC is reviewed.

Three scenarios for reducing energy consumption and CO₂ emissions are proposed and evaluated using strengths, weaknesses, opportunities and threats (SWOT) as well as the political, economic, social, technical, legal and environmental (PESTLE) frameworks.

The first scenario found that using solar Photovoltaic (PV) or hybrid solar PV and wind system to power household lighting could save significant amounts of energy, based on lighting making up between 8% to 30% of electricity consumption in GCC households. The second scenario considers replacement of conventional appliances with energy-efficient ones that use around 20% less energy. The third scenario looks at influencing consumer behavior towards sustainable energy consumption.

Pilot trials of these scenarios are recommended for a number of households. Then the results and feedback could be used to launch the schemes GCC-wide.

The proposed scenarios are designed to encourage responsible electricity consumption and production within households (SDG12).

All three proposals are found viable for policymakers to implement. However, to ensure successful implementation GCC Governments are recommended to review all the opportunities and challenges associated with these schemes as laid out in this paper.

Using building information modelling (BIM) technology, a conventional structure in this study was converted into a green building to measure its energy usage and CO2 emissions.

Digital images of the existing building conditions were captured using unmanned aerial vehicle (UAV), and were fed into Meshroom to generate the building’s geometry for 3D parametric model development. The model for the existing conventional building was created and converted to an energy model and exported to gbXML in Autodesk Revit for a whole building analysis which was carried out in the Green Building Studio (GBS). In the GBS, the conventional building was retrofitted into a green building to explore their energy consumption and CO2 emission.

By comparing the green building model to the conventional building model, the research found that the green building model saved 25% more energy while emitting 46.8% less CO2.

The study concluded that green building reduces energy consumption, thereby reducing the emission of CO2 into the environment. It is recommended that buildings should be simulated at the design stage to know their energy consumption and carbon emission performance before construction.

Occupant satisfaction, operation cost and environmental safety are essential for sustainable or green buildings. Green buildings increase the standard of living and enhance indoor air quality.

This investigation aided in a pool of information on how to use BIM methodology to retrofit existing conventional buildings into green buildings, showing how green buildings save the environment as compared to conventional buildings.

Energy-related financial literacy (ERFL) which consists of energy literacy, financial literacy and lifecycle cost literacy, can play an instrumental role in addressing climate change by ensuring efficient energy consumption (macro level benefit) and promoting financial well-being (micro level benefit) of households. This study aims to highlight the ERFL level and its effect on the energy consumption of the sample households in the state of West Bengal, India.

The study used primary data on 155 sample households from the two districts, i.e. Hooghly and North 24 Parganas in West Bengal, India, surveyed from September 2022 to November 2022 using a structured questionnaire. The study used the conceptual framework suggested by Blasch et al. (2018) to measure the ERFL. Pertinent statistical techniques and the ordinary least square regression method were used to attain the objectives of the study.

The outcome of the study showed that the average ERFL score was found to be moderate (63%). The findings of the study also indicated that the ERFL exerts a positive influence on reducing energy consumption among the sample households in India.

There is a dearth of research studies on the topic of ERFL around the globe. The very few studies so far conducted are mostly in the context of European economies and Nepal. Perhaps, to the best of the our knowledge, this is the first study on the issue of ERFL in the Indian context. Therefore, the present study will make an original contribution to the small but growing scholarship on ERFL.

Sub-Saharan Africa is a region that is highly vulnerable to the effects of climate change. Renewable energy consumption could play a major role in mitigating the effects of climate change by improving environmental quality in the region. The purpose of this paper is to examine the effect of renewable energy consumption on environmental quality in sub-Saharan African countries.

The empirical investigation is based on the estimation of an augmented Green Solow model through the defactored instrumental variables approach on a sample of 34 countries over the period 1996 to 2018.

The results of two-stage defactored instrumental variables estimator show that renewable energy consumption improves environmental quality. Indeed, renewable energies have a significant negative influence on CO₂ emissions. This result is robust when using the ecological footprint as an indicator of environmental quality.

In terms of implications, governments in Sub-Saharan Africa need to pursue policies to encourage investment in the renewable energy sector. This will promote renewable energy consumption, change the structure of the energy mix in favour of renewable energy, improve environmental quality and effectively combat climate change.

The originality of this research in relation to the existing literature lies at several levels. Firstly, the analysis is carried out using a unified framework combining the environmental Kuznets curve and the environmental convergence hypotheses. Secondly, this research uses a very recent econometric method. Finally, environmental quality is measured using two indicators.