Global Point Source CO₂ Emissions Monitoring Based on Hyperspectral Remote Sensing Imagery

Abstract. This study presents a hyperspectral remote sensing approach for monitoring global CO₂ point source emissions using China’s GF5 and ZY1 satellites. By applying the matched filter method in the 1.6 μm and 2.0 μm absorption band and the Integrated Mass Enhancement (IME) technique, this study successfully detects and quantifies emissions from multiple facilities within a single scene—demonstrated in a high-density industrial cluster in Xinjiang. Results show current systems can detect power plants with annual emissions above 2.90 MtCO₂, covering 6.74 GtCO₂/year globally across eight sectors. While power and chemical sectors are well captured, cement and petrochemical emissions remain poorly detected, highlighting the need for improved sensitivity to low-intensity sources.