<p>Somalia stands at a critical juncture, balancing post-conflict reconstruction with extreme environmental vulnerability. However, the absence of empirical evidence on the drivers of CO₂ emissions severely hampers sustainable policymaking. Using the Autoregressive Distributed Lag (ARDL) approach on time-series data from 1980 to 2021, this study provides the first comprehensive analysis of the integrated effects of GDP growth, industrialization, energy use, and urbanization on CO₂ emissions in Somalia. The long-run results reveal that energy use and urbanization are the most significant determinants of emissions. A 1% increase in energy use and urbanization increases CO₂ emissions by 0.831% and 1.657%, respectively. In contrast, GDP growth and industrialization show no significant long-run impact. The model's error correction term is significant (− 0.487), indicating that the system corrects towards long-run equilibrium at a rate of 48.7% per year. Furthermore, Granger causality analysis identifies unidirectional causality running from energy use, urbanization, and industrialization to CO₂ emissions. A reverse causality from CO₂ emissions to GDP growth suggests that environmental policies may impact the nation's fragile economic recovery. These results are instrumental for formulating Somalia's first evidence-based climate and development policies. Key policy initiatives should include prioritizing investment in renewable energy (particularly solar) to reduce reliance on fossil fuels; implementing sustainable urban planning to manage rapid population concentration; and designing development strategies that proactively decouple economic reconstruction from future carbon-intensive pathways. Establishing a robust data and monitoring framework is also critical for future policy evaluation.</p> Graphical abstract <p></p>