Historical trends, underlying factors and the 2035 horizon situation of GHG emission in 16 Middle Eastern nations

Abstract

This research examines GHG emissions across 16 Middle Eastern countries from 1990 to 2021 and projects emissions up to 2035. Utilizing artificial neural networks (ANN) and regression models, it assesses the influence of urban/rural populations, GDP per capita, energy intensity, and carbon intensity on emissions. The ANN with two hidden layers outperformed other models in 63 % of cases. Per capita emissions grew most in Oman, Saudi Arabia, and Iran, while the United Arab Emirates (ARE), Bahrain, and Qatar saw declines. A positive correlation between GDP and energy consumption was noted, with Iran showing the strongest correlation. All countries exhibited a positive relationship between carbon emissions and energy consumption, particularly in conflict-affected nations. Energy intensity has risen in Oman, Iran, Saudi Arabia, the ARE, and Lebanon. The carbon intensity of Middle Eastern countries, excluding Yemen, has demonstrated a downward trend, indicating a shift towards renewable energy. Projections of GHG emissions using ANN and multiple linear regressions (MLR) suggest a 35% increase by 2035compared to 2021 under a business-as-usual scenario, while an emission reduction scenario could lower emissions by 10.82 %, potentially reaching about 4.8 gigatonnes of CO_2e. In the Middle East, the anticipated emissions align closely with the SSP3-7.0 pathway, which faces significant mitigation and adaptation challenges.