Aircraft and satellite observations reveal historical gap between top-down and bottom-up C[O.sub.2] emissions from Canadian oil sands
Measurement-based estimates of greenhouse gas (GHG) emissions from complex industrial operations are challenging to obtain, but serve as an important, independent check on inventory-reported emissions. Such top-down estimates, while important for oil and gas (O&G) emissions globally, are particu...
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Veröffentlicht in: | PNAS nexus 2023-05, Vol.2 (5) |
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Zusammenfassung: | Measurement-based estimates of greenhouse gas (GHG) emissions from complex industrial operations are challenging to obtain, but serve as an important, independent check on inventory-reported emissions. Such top-down estimates, while important for oil and gas (O&G) emissions globally, are particularly relevant for Canadian oil sands (OS) operations, which represent the largest O&G contributor to national GHG emissions. We present a multifaceted top-down approach for estimating C[O.sub.2] emissions that combines aircraft-measured C[O.sub.2]/N[O.sub.x] emission ratios (ERs) with inventory and satellite-derived N[O.sub.x] emissions from Ozone Monitoring Instrument (OMI) and TROPOspheric Ozone Monitoring Instrument (TROPOMI) and apply it to the Athabasca Oil Sands Region (AOSR) in Alberta, Canada. Historical C[O.sub.2] emissions were reconstructed for the surface mining region, and average top- down estimates were found to be >65% higher than facility-reported, bottom-up estimates from 2005 to 2020. Higher top-down vs. bottom-up emissions estimates were also consistently obtained for individual surface mining and in situ extraction facilities, which represent a growing category of energy-intensive OS operations. Although the magnitudes of the measured discrepancies vary between facilities, they combine such that the observed reporting gap for total AOSR emissions is [greater than or equal to] (31 [+ or -] 8) Mt for each of the last 3 years (2018-2020). This potential underestimation is large and broadly highlights the importance of continued review and refinement of bottom- up estimation methodologies and inventories. The ER method herein offers a powerful approach for upscaling measured facility-level or regional fossil fuel C[O.sub.2] emissions by taking advantage of satellite remote sensing observations. Keywords: greenhouse gas, oil and gas, carbon dioxide, remote sensing, aircraft study |
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ISSN: | 2752-6542 2752-6542 |
DOI: | 10.1093/pnasnexus/pgad140 |