The role of renewable versus non-renewable energy to the level of CO2 emissions a panel analysis of sub- Saharan Africa’s Βig 10 electricity generators

Inglesi‐Lotz, Roula; Doğan, Eyüp

doi:10.1016/j.renene.2018.02.041

Cited by 487 publications

(137 citation statements)

References 78 publications

Supporting

Mentioning

116

Contrasting

Order By: Relevance

“…The corresponding effects in the long run are 0.528, 0549 and 0.101%. The results are in line with those of most studies in the literature such as Shahbaz et al[20], Farhani et al[27], Heidari et al[15], Inglesi-Lotz and Dogan[44] who find that energy consumption increases environmental degradation.Our result is attributed to the fact that the Algerian, Egyptian and South African economies are primarily based on the exploitation and the exports of fossil ener-…”

supporting

confidence: 92%

Energy Consumption, Economic Growth and Carbon Emissions: Evidence from the Top Three Emitters in Africa

Nkengfack¹,

Fotio²

2019

View full text Add to dashboard Cite

This study analyses the cointegration and the causal relationship between energy consumption, economic growth and carbon emissions, using aggregate and disaggregate measures of energy consumption for Algeria, Egypt and South Africa over the period 1971-2015. Based on the ARDL, our results show that aggregate energy consumption and economic growth have positive and significant impacts on carbon dioxide (CO 2) both in the long and short run in those countries. At the disaggregated level, the main energy-related drives of carbon emissions are oil, electricity and coal consumption in Algeria, Egypt and South Africa, respectively. In addition, the implementation of the Toda-Yamamoto test for causality reveals the existence of several types of relationship between CO 2 emissions, economic growth and energy consumption.

show abstract

supporting

confidence: 92%

Energy Consumption, Economic Growth and Carbon Emissions: Evidence from the Top Three Emitters in Africa

Nkengfack¹,

Fotio²

2019

View full text Add to dashboard Cite

show abstract

“…It appears that promoting renewable energy in some low-income countries may lead to restrain their economic progress in the short run. Inglesi-Lotz and Dogan (2018) suggested that shifting energy consumption away from fossil fuels to renewable energy sources is a challenge for developing countries. Different energy structures between the developing and developed countries are different because of technological and economic conditions.…”

Section: Literature Reviewmentioning

confidence: 99%

The relationship between energy consumption, economic growth and carbon dioxide emissions in Pakistan

2020

View full text Add to dashboard Cite

Developing countries are facing the problem of environmental degradation. Environmental degradation is caused by the use of non-renewable energy consumptions for economic growth but the consequences of environmental degradation cannot be ignored. This primary purpose of this study is to investigate the nexus between energy consumption, economic growth and CO 2 emission in Pakistan by using annual time series data from 1965 to 2015. The estimated results of ARDL indicate that energy consumption and economic growth increase the CO2 emissions in Pakistan both in short run and long run. Based on the estimated results it is recommended that policy maker in Pakistan should adopt and promote such renewable energy sources that will help to meet the increased demand for energy by replacing old traditional energy sources such as coal, gas, and oil. Renewable energy sources are reusable that can reduce the CO2 emissions and also ensure sustainable economic development of Pakistan.

show abstract

“…Many scholars conducted in-depth studies on the factors that affect carbon emissions [5][6][7][8]. Many studies show that energy consumption is the main factor affecting carbon emissions [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Forecasting Carbon Emissions Related to Energy Consumption in Beijing-Tianjin-Hebei Region Based on Grey Prediction Theory and Extreme Learning Machine Optimized by Support Vector Machine Algorithm

Wang

et al. 2018

Energies

View full text Add to dashboard Cite

Carbon emissions and environmental protection issues have brought pressure from the international community during Chinese economic development. Recently, Chinese Government announced that carbon emissions per unit of GDP would fall by 60–65% compared with 2005 and non-fossil fuel energy would account for 20% of primary energy consumption by 2030. The Beijing-Tianjin-Hebei region is an important regional energy consumption center in China, and its energy structure is typically coal-based which is similar to the whole country. Therefore, forecasting energy consumption related carbon emissions is of great significance to emissions reduction and upgrading of energy supply in the Beijing-Tianjin-Hebei region. Thus, this study thoroughly analyzed the main energy sources of carbon emissions including coal, petrol, natural gas, and coal power in this region. Secondly, the kernel function of the support vector machine was applied to the extreme learning machine algorithm to optimize the connection weight matrix between the original hidden layer and the output layer. Thirdly, the grey prediction theory was used to predict major energy consumption in the region from 2017 to 2030. Then, the energy consumption and carbon emissions data for 2000–2016 were used as the training and test sets for the SVM-ELM (Support Vector Machine-Extreme Learning Machine) model. The result of SVM-ELM model was compared with the forecasting results of SVM (Support Vector Machine Algorithm) and ELM (Extreme Learning Machine) algorithm. The accuracy of SVM-ELM was shown to be higher. Finally, we used forecasting output of GM (Grey Prediction Theory) (1, 1) as the input of the SVM-ELM model to predict carbon emissions in the region from 2017 to 2030. The results showed that the proportion of energy consumption seriously affects the amount of carbon emissions. We found that the energy consumption of electricity and natural gas will reach 45% by 2030 and carbon emissions in the region can be controlled below 96.9 million tons. Therefore, accelerating the upgradation of industrial structure will be the key task for the government in controlling the amount of carbon emissions in the next step.

show abstract

The role of renewable versus non-renewable energy to the level of CO2 emissions a panel analysis of sub- Saharan Africa’s Βig 10 electricity generators

Cited by 487 publications

References 78 publications

Energy Consumption, Economic Growth and Carbon Emissions: Evidence from the Top Three Emitters in Africa

Energy Consumption, Economic Growth and Carbon Emissions: Evidence from the Top Three Emitters in Africa

The relationship between energy consumption, economic growth and carbon dioxide emissions in Pakistan

Forecasting Carbon Emissions Related to Energy Consumption in Beijing-Tianjin-Hebei Region Based on Grey Prediction Theory and Extreme Learning Machine Optimized by Support Vector Machine Algorithm

Contact Info

Product

Resources

About