Estimation of gas emissions from a waste pond using micrometeorological approaches: Footprint sensitivities and complications

The quantification of gas emissions from waste storage and treatment ponds is an important problem. The objective of this study was to better understand the use of micrometeorological techniques for this purpose. Methane emissions were estimated from a large tailings pond (surface area >11 km²) at an oil sands mine site using datasets collected by different groups over a nine-month period. Emissions were calculated with eddy-covariance (EC) and inverse dispersion modelling (IDM) techniques. Three different IDM calculations were made using methane concentrations measured with either fixed-point sensors (IDM-LGR), a long-path laser (IDM-GL), or an unmanned aerial vehicle (IDM-UAV). Emissions were also estimated from a flux-chamber (FC) survey. Although the temporal overlap between the different datasets was limited, the results indicate substantial differences in emission-rate estimates. During a summer interval the EC, IDM-LGR, and IDM-GL estimates were 19%, 41%, and 56% of the FC-estimated rate, respectively. The overall ordering was EC ≈ IDM-UAV < IDM-LGR < IDM-GL < FC. Differences in the emission estimates appear to be explained by the physical location of the measurement footprints. The EC and IDM-UAV footprints were comparably small and confined to lower emitting areas of the pond, while the larger IDM-LGR and IDM-GL footprints included higher emitting areas. It would seem sensible to prefer the larger footprint IDM approaches for this large pond. However, the large IDM footprints necessitated a complicated analysis to remove the influence of an adjacent methane source in the calculations. This study illustrates the importance of understanding the footprint of micrometeorological techniques when quantifying emissions and the complications that arise when the footprint does not match the source area.