Artificial intelligence-driven insights: Precision tracking of power plant carbon emissions using satellite data

Abstract

Human activities have been driving massive greenhouse gas emissions, causing global warming, and triggering increasingly frequent extreme weather events that severely threaten the environment. Power generation is the leading contributor to anthropogenic emissions, making precise, real-time measurement and monitoring of power plant carbon emissions crucial in reducing climate change. This study uses a new sophisticated pipeline that combines tropospheric monitoring instrument satellite data, power plant attributes, and advanced artificial intelligence algorithms to build a predictive carbon emission model. The approach utilizes multimodal data processing, encoding, and model optimisation. Experimental results confirm that this pipeline can automatically extract and utilize vast amounts of relevant data, thereby enabling the artificial intelligence model to accurately predict power plant carbon emissions and providing a vital tool for reducing global warming.