Assessing Sub-Saharan Africa's low carbon development through the dynamics of energy-related carbon dioxide emissions

One major drawback of climate change agreements including the recent 21st Conference of the Parties is focusing mainly on countries or regions with very high contribution to global emission rise but neglecting potential emitters. With Sub-Saharan Africa (SSA) been one such potential region, this paper applies the extended Kaya Identity Decomposition to investigate the dynamic impact of energy-related driving factors on carbon dioxide (CO2) emissions and its future trend in SSA. Employing the Autoregressive distributed lag model analysis for the period 1980 to 2014 reveals carbon intensity and "transition from biomass to fossil fuel energy" as the major long run and short run drivers of CO2 emissions increase respectively while "potential of penetration of clean energy in the energy consumption mix" is the only driver of both short and long run CO2 emissions decrease. Energy intensity and per capita GDP (supported by substantial household self-consumption of fuel) weakly and positively impact CO2 emissions in SSA. The dynamic forecasting analysis reveals possible low carbon energy path towards 2030. We propose transport sector energy efficiency improvement, use of natural gas and renewables to improve the region's high energy poverty, improvement of household-self consumption paying attention to cleaner and safer energy and others. (C) 2020 Elsevier Ltd. All rights reserved.