This study presents a regional bottom-up model for assessing space cooling energy and related greenhouse gas emissions. The model was developed with the aim of improving the quality and quantity of cooling energy and emission data, especially for the benefit of local decision making. Based on a benchmarking study, a representative archetype was developed, simulation software used and linear statistical model constructed. This model explores the way in which CO2 emission levels are affected by different energy efficiency measures to reduce cooling energy consumption in buildings. The analysis showed that improving building energy efficiency could generate considerable carbon emissions reduction credits with competitive benefit. The developed model was found to be capable in selecting cost-effective, environmentally-preferred building efficiency measures and evaluating the future trend of CO2 emissions in the residential building of Al-Ain city
