A growing fleet of satellite and airplane missions is measuring surface-scattered sunlight in a top-down viewing geometry to identify and quantify emission plumes of the driving anthropogenic greenhouse gases carbon dioxide (CO2) and methane (CH4). Emission estimates based on plume imagery have proven valuable complementary information to bottom-up estimates from emission inventories. In addition, airborne instruments cover large areas in a short time. Still, satellites with point source imaging capabilities re-visit an exact geolocation only once in several days, causing them to observe emission snapshots that lack information on the intermittency and variability of the sources on shorter time scales.
We developed a prototype technique that uses a ground-based, stationary hyperspectral camera for plume imagery of strong point sources. This technique allows observing the short-term variability of a single source with remote sensing as complementary information to the global coverage of satellite data. I will present the method employed in my Ph.D. to reliably image CO2 and CH4 plumes in the atmosphere and estimate emissions from them on time scales from minutes to hours. The talk features results of field campaigns at a coal-fired power plant in Mannheim, Germany, and coal mining operations in the Upper Silesian Coal Basin, Poland.