Methane (CH4) is the second most important anthropogenic greenhouse gas and atmospheric concentrations have increased at record rates in recent years. This talk will explore the use of remote sensing to estimate anthropogenic methane emissions. The first part will highlight results from a recent study that uses satellite measurements of CH4 and other trace gases to estimate enhancement ratios in urban areas. These enhancement ratios are compared to bottom-up gridded emission inventories to identify discrepancies and suggest improvements. The second part will introduce a top-down hierarchical Bayesian inverse model for partitioning oil and gas CH4 emissions with ethane (C2H6) measurements. It will demonstrate an application of this model to CH4 emissions in Alberta & Saskatchewan using measurements from the Total Carbon Column Observing Network (TCCON).
Estimating Methane Emissions with Remote Sensing of Multiple Trace Gases
Host: Eylon Vakrat