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Abstract

This study presents ground-based imaging of carbon dioxide (CO2) and methane (CH4) plumes to derive emission estimates of localized sources. Employing a stationary spectral camera enables rapid scene scanning at approximately one-minute intervals, capturing sky-scattered sunlight in the shortwave infrared spectral range. The developed processing pipeline converts raw hyperspectral data into emission estimates, utilizing an adapted matched filter retrieval for quantifying atmospheric enhancements in CO2 and CH4 plumes. The technique facilitates high-frequency imaging of individual sources, thereby complementing existing greenhouse gas monitoring methods like satellite snapshot images. Field campaigns at point sources of CO2 andCH4 show the method’s capability. Observing coal mining emissions demonstrates the detection and quantification of CH4 plumes in single scans, even under challenging conditions. Emission estimates obtained through mass balance methods provide sub-hourly temporal resolution. They reveal considerable diurnal (up to 55 %) and day-to-day (1.56 tCH4 h−1 to 4.57 tCH4 h−1) source variability, emphasizing the added value of high-frequent emission monitoring. A proof-of-concept study at a coal-fired power plant provides the first ground-based imaging observations of CO2 plumes. CO2 emission estimates require hourly-averaged measurements and a specifically designed observation forward model. The retrieved emissions show reasonable agreement with validation data under favorable conditions, following the power plant’s temporal variability and averaging 84 % of the expected emissions with a mean relative uncertainty of 24 %.