Space-based assessment of NOx emissions from global oil and gas fields: Bridging the gap in current emission inventories

Abstract

Identifying air pollutant sources and quantifying related emissions provides crucial information towards improving global air quality and public health. However, emission inventories for oil and gas (OG) activities inadequately represent nitrogen oxide (NO_x) emissions—a key precursor to tropospheric ozone and secondary aerosols—with notable discrepancies identified. Satellite remote sensing provides a unique vantage point to map and quantify these emissions consistently on a global scale. Here, we quantify annual NO_x emissions from 44 major OG basins distributed globally, utilizing TROPOspheric Monitoring Instrument (TROPOMI) nitrogen dioxide (NO₂) observations with the divergence flux method. In addition, we use the spaceborne Visible Infrared Imaging Radiometer Suite (VIIRS) natural gas flaring detections to further constrain satellite-derived NO_x emissions. The divergence flux method, which addresses 3D topography corrections and chemical loss of NO_x while accounting for wind-induced flux smearing, provides a robust approach for estimating NO_x emissions. This top-down approach resolves emissions at the facility and basin scale (0.01° x 0.01°), enabling direct quantification of a major gap in current bottom-up inventories. Our findings reveal significant differences between satellite observations and established inventories, which systematically underestimate OG sector emissions. A direct comparison of our TROPOMI-derived NO_x emissions against the existing inventories suggests that EDGARv6.1 underestimates onshore emissions by 61 % and offshore emissions by 26 %. The discrepancy is even more pronounced for the CAMS-GLOB-ANT_v5.3 inventory, which underestimates onshore and offshore emissions by 78 % and 92 %, respectively. These findings hold significance for global emission assessments, demonstrating that current inventories are missing a substantial source of NO_x pollution, particularly from OG fields. Furthermore, our approach provides detailed spatial emission maps that enhance the granularity in depicting NO_x distribution with error analysis (uncertainties: 32 %-54 %) supporting that inventory discrepancies are statistically significant, representing structural deficiencies rather than measurement error. We further explore the variations in the correlation between NO_x emissions with OG production volumes and CH₄ concentrations across different OG basins in North America. The observed co-locations and correlations provide important insights into co-pollution emission characteristics of methane and NO_x, that are respectively a potent greenhouse gas and a reactive air quality pollutant, linked to be originating from oil and gas activity. These findings have important implications for regulatory monitoring and verification, particularly for addressing emissions transparency requirements under international climate frameworks.