Exploring machine learning models for predicting greenhouse gas emissions in Africa’s building sector: A case study of six nations
Abdullahi Mohamud Adam·Farhad Bolouri·Abdullahi Ilyas Osman·Hüseyin Gökçekuş·Abdinasir Mohamed Yusuf
Abstract The building sector plays a crucial role in urbanization and economic growth. However, the sector is a major emitter of greenhouse gases and dependent on fossil fuel energy. In 2022, it accounted for 37% of global energy and process-related CO 2 emissions, underscoring its impact on climate change. This study aims to predict greenhouse gas emissions from buildings across six African nations—Nigeria, Algeria, South Africa, Egypt, Ethiopia, and Morocco—using time series data spanning from