The concept of environmental sustainability aims to achieve economic development while achieving a sustainable environment. The inverted U-shape relationship between economic growth and environmental quality, also called Environmental Kuznets Curve (EKC), describes the correlation between economic growth and carbon emissions. This study assesses the role of agriculture and energy-related variables while evaluating the EKC threshold in 54 African economies, and income groups, according to World Bank categorization, including low income, lower-middle, upper-middle, and high-income in Africa. With 1990–2015 panel data, the results are estimated using panel cointegration, Fully Modified Ordinary Least Square (FMOLS), and granger causality tests. The results are: (1) The study validated the EKC hypothesis in the low-income, lower-, and upper-middle-income economies. However, there is no evidence of EKC in the full African and high-income panels. Furthermore, the turning points of EKC in the income group are meagerly low, showing that Africa could be turning on EKC at lower income levels. (2) The correlation between agriculture with CO2 is found positive in the high-income economy. However, agriculture has a mitigation effect on emissions in the lower-middle-income and low-income economies, and the full sample. Also, renewable energy is negatively correlated with emissions in Africa and the high-income economy. In contrast, non-renewable energy exerts a positive effect on emissions in all income groups except the low-income economies.

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Economic growth and industrialization often default to a great dependency on fossil fuels (FF) to supply power needs. The carbon rich nature of FF combustion can impact global warming. Therefore, it is conducive to transition from FF to renewable energy (RE). The present study aimed to address if replacement of a single FF by RE can mitigate carbon emissions. We conduct the study in a country undergoing mass urbanization and challenging energy demands. Data from energy resources in the Power & Energy Sector Master Plan (PSMP2016; Bangladesh) are analyzed over the 2017-2021 trajectory. Two scenarios for imports, oil and coal are assessed. Environmental input output (E-IO) analysis and percentage equivalence analysis measured data variables. The data is then further disaggregated into an emission reduction (ER) model with sensitivity analysis to measure carbon emission reduction when each FF source is substituted by RE. Results show the percentage share of energy generation capacity by both coal and RE increase over time. Solar and wind power contribute to the increase in RE. When oil is imported a 1% increase in oil, coal, and gas-based energy generation capacity increases carbon emissions by 1.25%, 1.48% and 0.93%, respectively. 1% increase in RE produces negligible carbon emissions (0.0042%). There was little difference in the percentages of carbon emissions when coal is imported. Substituting any FF with RE of equal energy capacity does not, in the short term, reduce carbon emissions in either scenario. Therefore, we conclude that for long term clean energy prospects in Bangladesh, RE needs to be developed to operate at greater capacity in conjunction with other carbon management factors. The research findings herein offer insights for clean energy implementation in developing nations.