In:
PNAS Nexus, Oxford University Press (OUP), Vol. 2, No. 5 ( 2023-05-02)
Abstract:
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 CO2 emissions that combines aircraft-measured CO2/NOx emission ratios (ERs) with inventory and satellite-derived NOx 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 CO2 emissions were reconstructed for the surface mining region, and average top–down estimates were found to be & gt;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 ≥(31 ± 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 CO2 emissions by taking advantage of satellite remote sensing observations.
Type of Medium:
Online Resource
ISSN:
2752-6542
DOI:
10.1093/pnasnexus/pgad140
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2023
detail.hit.zdb_id:
3120703-0
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