Monitoring and quantifying CO2 emissions of isolated power plants from space

CO2 emissions of power plants are often self-reported and calculated based on fuel consumption. The authenticity of CO2 emission data from power plants are preferable to be verified by independent measurements. Satellite observations can provide these CO2 emission observations from isolated power plants. However, there are two difficulties in the current top-down anthropogenic CO2 emission inversions, that is, (1) the anthropogenic CO2 emission signal is difficult to distinguish from the background of other emitted CO2, and (2) the temporal and spatial resolution of CO2 satellite observation data are currently limited. In this study, we focus on how to improve the accuracy of CO2 emissions using different methods and wind data estimates. We assess these emission estimates by comparison with USA EPA emission data, and identify and explore suitable cases elsewhere in the world. We have selected only isolated power plants for this study, to avoid complications because of multiple sources in close proximity. We first compare the Gaussian plume model and cross-sectional flux methods for estimating CO2 emissions of power plants. Then we examine the sensitivity of the emission estimates to possible choices for the wind field. For verification we have used power plant emissions that are reported on an hourly basis by the Environmental Protection Agency (EPA) in the United States. By using the OCO-2 and OCO-3 observations over the past four years we identified emission signals of isolated power plants and arrived at a total of 50 collocated cases involving 22 power plants. We found the wind field halfway the height of planetary boundary layer (PBL) yielded the best results. We found that the instantaneous satellite estimated emissions of these 50 cases and reported emissions display a weak correlation (R2=0.12). The correlation improves with averaging over multiple observations of the 22 power plants (R2=0.40). The method was subsequently applied to 106 power plants cases worldwide. We demonstrate that accurate estimation of power plant emissions can be achieved by monitoring from future satellite missions with more frequent observations.