Boxed-in: Comparing Algorithms for Box-flight Mass-Balance Greenhouse Gas Flux Measurements from Mineable and In Situ Oil Sands Developments
Creators: Erland, Broghan
Publisher: name: University of Alberta Library
Year: 2022

<p>To combat global warming, Canada has committed to reducing greenhouse gases (GHGs) 40-45% below 2005 emission levels by 2025. Monitoring emissions and deriving accurate inventories are essential to reaching these goals. GHGs can be measured at a small scale, often using ground measurements which are extrapolated to estimate regional emissions, or at larger scales using airborne or satellite methods to infer area sources. Airborne methods can provide regional and area source measurements if ideal conditions for sampling are met. For the first time, two airborne mass-balance box-flight algorithms were compared to assess the extent of their agreement and their performance under various conditions. The Scientific Aviation, SciAv Gaussian algorithm and the Environment and Climate Change Canada top-down emission rate retrieval algorithm (TERRA) were applied to data from five samples. Estimates were compared using standard procedures, by systematically testing other method fits, and by investigating the effects on the estimates when method assumptions were not met. Results indicate that in standard scenarios the SciAv and TERRA mass-balance, box-flight methods produce similar estimates that agree (3-25%) within model errors (4-34%). Implementing a surface extrapolation procedure for the SciAv model may improve emission estimation. Models disagreed when non-ideal conditions occurred (under non-stationary conditions). Results from both models were largely unusable when a flight sample did not capture the top of an emission plume. Overall, the results provide confidence in the box-flight methods, and indicate that emissions estimates are not overly sensitive to the choice of algorithm, but demonstrate that fundamental model assumptions should be assessed for each flight. The box-flight mass-balance airborne methods provide in-depth measurements by flying around a source to box in an emission plume. They can attain a low uncertainty (~ 2 %), but they require known sources, often require advance coordination with industry, and are quite expensive, so cannot always be easily applied. A different airborne method, airborne imaging spectroscopy, takes a snapshot from above to estimate emissions, can sample large areas quickly, and can capture unknown emissions leaks and sources, but currently has larger uncertainty in emission estimates than mass-balance methods (&lt;20%). Using a spectral remote instrument, the Airborne Visible InfraRed Imaging Spectrometer - Next Generation (AVIRIS-NG), an independent sample captured a large sporadic emission 4-7 times larger than the SciAv sample three days later. The range in estimates highlights the utility of supplementing airborne mass balance methods with other methods to get a more complete understanding of emissions. Both methods are limited by intermittent sampling and cannot be solely used to characterize day-to-day emissions operations, or seasonal variability. Current national emissions inventories could be improved by incorporating independent airborne samples for validation of independent repeated and, or continuous ground, and satellite measurements with industry-reported inventories to provide better estimates. Advances in developing inventories using a combination of defendable methods at varying scales of measurement will enable more accurate and complete estimation of GHG fluxes, while holding nations and industry accountable to their emissions. These changes would be key steps to reducing emissions and addressing climate change goals.</p>