The average population in sub-Saharan Africa that has access to clean fuel for cooking and technology is 23.6%. This study examines the panel data for 29 sub-Saharan African (SSA) countries for the period 2000-2018 to estimate impacts of clean energy technologies on environmental sustainability measured by load capacity factor (LCF) to capture both nature's supply and man's demand for the environment. The study used generalized quantile regression, which is more robust to outliers and eliminates the endogeneity of variables in the model using lagged instruments. Results show that clean energy technologies (clean fuels for cooking and renewable energy) have positive and statistically significant impacts on environmental sustainability in SSA for almost all quantiles. For robustness checks, we used Bayesian panel regression estimates and the results remained unchanged. The overall results suggest that clean energy technologies improve environmental sustainability in SSA. The result shows a U-shaped relationship between environmental quality and income and confirms the Load Capacity Curve (LCC) hypothesis in SSA, which implies that income first worsens environmental sustainability and then, after exceeding certain quantiles, improves environmental sustainability. On the other hand, the results also confirm the environmental Kuznet curve (EKC) hypothesis in SSA. The findings show the importance of using clean fuels for cooking, trade, and renewable energy consumption in improving environmental sustainability in the region. The policy implication is that governments in SSA should reduce the cost of energy services (i.e., renewable energy and clean fuels for cooking) to achieve greater environmental sustainability in the region.

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http://dx.doi.org/10.1007/s11356-023-28438-4DOI Listing

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