Document
Metadata
Category
Environmental Science and Climate Change
Authors
Mohamed Abdi Abdullahi, Abdisalam Hassan Muse, Yahye Hassan Muse, Mukhtar Abdi Hassan & Saralees Nadarajah
Title
Forecasting the 2030 Climate Trajectory: Spatio-Temporal Analysis of Greenhouse Gas Emissions in East Africa (IGAD)
Journal
Earth Systems and Environment
Year of Publication
2026
Abstract
The Intergovernmental Authority on Development (IGAD) region in East Africa faces acute susceptibility to climate change, making the understanding of greenhouse gas (GHG) emission trajectories essential for effective mitigation and adaptation planning. While Africa’s contribution to global emissions remains historically low, recent trends show an accelerating rate of increase. This study analyzes historical GHG emissions from 1990 to 2023 and establishes a robust multi-model framework to project emissions through 2030 for all eight IGAD member states. The primary objective is to provide evidence-based insights aligned with 2030 Sustainable Development Agenda. Historical trends were evaluated using the non-parametric Mann-Kendall test and Theil-Sen slope estimator. A competitive forecasting approach assessed ARIMA, ETS, NNAR, and Theta models for each country. The best model was selected based on the Symmetric Mean Absolute Percentage Error (sMAPE) to ensure scale-independent accuracy, with the understanding that these forecasts represent a ‘Business-As-Usual’ baseline rather than definitive predictions. Furthermore, spatial patterns of forecasted emissions were analyzed using Local Moran’s I and the Getis-Ord Gi* statistically to identify statistically significant clusters. The results reveal a significant increasing trend in total GHG emissions for the IGAD region, with an average rise of 11.01 million tonnes of CO₂ equivalent per year (p < 0.001). Country-level analyses demonstrate considerable heterogeneity; while Ethiopia and Kenya show steep upward trajectories, Sudan displays potential stabilization. Conditional forecasts indicate continued emission growth for most member states through 2030. Crucially, the spatial autocorrelation analysis identifies a significant transboundary “hot spot” of high emissions encompassing Ethiopia, Kenya, Uganda, Somalia, and Djibouti, contrasting with a “cold spot” in the north-western region (Sudan and South Sudan). These findings suggest that emission dynamics are spatially clustered, highlighting the potential benefits of shifting from isolated national interventions to regionally coordinated climate policies that target these identified cross-border patterns. This visual summary presents the integrated spatio-temporal framework and key findings of the study on greenhouse gas (GHG) emissions in East Africa. The workflow illustrates the transition from data acquisition to policy-relevant insights. The process begins with historical emission data (1990–2023) for eight IGAD member states, establishing a baseline. This dataset undergoes a dual-stream analysis: a temporal evaluation using the Mann-Kendall test and Theil-Sen estimator to quantify trends, and a spatial assessment using Local Moran’s I and Getis-Ord Gi* to detect geographic clustering. At the core is the multi-model forecasting framework, where ARIMA, ETS, NNAR, and Theta models compete based on the lowest sMAPE to generate projections through 2030. The results visualization highlights the critical outcomes: the region is on a significant upward trajectory, with emissions rising by 11.01 million tonnes of CO₂ equivalent annually. Spatial maps reveal a statistically significant “hotspot” of high emissions clustering around Ethiopia, Kenya, Uganda, Somalia, and Djibouti, contrasting with a “coldspot” in Sudan and South Sudan. The graphic concludes by synthesizing these forecasts into a clear policy takeaway: the need for a regionally coordinated strategy targeting transboundary emission clusters.