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Abstract

Greenhouse gas (GHG) emissions are a key driver of global climate change, influencing temperature patterns, extreme weather events, and ecosystem stability. Monitoring and predicting GHG dynamics is therefore crucial for understanding and mitigating climate risks. Traditional methods of measuring GHG emissions, such as groundbased monitoring, are limited by spatial coverage and temporal resolution. Remote sensing technologies, however, offer a powerful alternative by providing comprehensive, real-time data on atmospheric GHG concentrations and their spatial distribution. This article explores the integration of remote sensing data with climate models to predict future climate risks, focusing on how this approach can enhance our understanding of GHG dynamics and improve mitigation and adaptation strategies. The paper discusses the applications of remote sensing in monitoring key GHGs like carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), examining their roles in climate processes and their implications for future climate scenarios. By synthesizing current research and technological advances, the study highlights the potential of remote sensing as a vital tool for climate risk prediction and effective climate policy formulation.