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Abstract

Climate change, driven largely by anthropogenic greenhouse gas (GHG) emissions, poses a critical threat to global ecosystems, economies, and human well-being. Reducing GHG emissions is central to mitigating climate change, but achieving significant reductions requires effective strategies informed by robust analytical tools. Model-based analysis offers valuable insights into how different reduction strategies impact emission trajectories and climate outcomes. This study explores the application of model-based analysis to evaluate various GHG emission reduction strategies across sectors such as energy, transportation, and land use. The results suggest that integrated approaches, which combine technological advancements with policy measures, offer the most promising pathways for reducing emissions in the short and long term. Additionally, the study highlights the importance of incorporating economic, technological, and societal factors into model-based simulations to ensure realistic and actionable strategies. These findings underscore the necessity of model-driven decision-making in the design and implementation of GHG reduction policies.