Preprints
https://doi.org/10.5194/acp-2022-599
https://doi.org/10.5194/acp-2022-599
 
10 Oct 2022
10 Oct 2022
Status: this preprint is currently under review for the journal ACP.

Identifying and accounting for the Coriolis Effect in satellite NO2 observations and emission estimates

Daniel A. Potts1, Roger Timmis2, Emma J. S. Ferranti3, and Joshua D. Vande Hey1,4 Daniel A. Potts et al.
  • 1School of Physics and Astronomy, University of Leicester, Leicester, UK
  • 2Environment Agency, c/o Lancaster University, Lancaster LA1 4YQ, UK
  • 3School of Engineering, University of Birmingham, Edgbaston B15 2TT, UK
  • 4Centre for Environmental Health and Sustainability, University of Leicester, Leicester, UK

Abstract. Recent developments in atmospheric remote sensing from satellites have made it possible to resolve daily emission plumes from industrial point sources, around the globe. Wind rotation aggregation coupled with statistical fitting is commonly used to extract emission estimates from these observations. These methods are used here to investigate how the Coriolis Effect influences the trajectory of observed emission plumes, and to assess the impact of this influence on satellite derived emission estimates. Of the 17 industrial sites investigated, nine showed the expected curvature for the hemisphere they reside in. Five showed no or negligible curvature, and two showed opposing or unusual curvature. The sites which showed conflicting curvature all reside in topographically diverse regions, where strong meso-gamma scale (2–20 km) turbulence dominates over larger synoptic circulation patterns. For high curvature cases the assumption that the wind-rotated plume aggregate is symmetrically distributed across the downwind axis breaks down, which impairs the quality of statistical fitting procedures. Using NOx emissions from Matimba power station as a test case, not compensating for Coriolis curvature resulted in an10 underestimation of ∼ 9 % on average for years 2018 to 2021. This study is the first formal observation of the Coriolis Effect and its influence on satellite observed emission plumes, and highlight both the variability of emission calculation methods and the need for a standardised scheme for this data to act as evidence for regulators.

Daniel A. Potts et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-599', Anonymous Referee #1, 16 Nov 2022
  • RC2: 'Comment on acp-2022-599', Anonymous Referee #2, 30 Nov 2022

Daniel A. Potts et al.

Daniel A. Potts et al.

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Short summary
With the launch of the TROPOspheric Monitoring Instrument (TROPOMI) in 2017, it is now possible to observe pollutants emitted from individual industrial facilities on a daily basis around the globe. By using observations of Nitrogen Dioxide (NO2) from 17 different industrial sites, we show how the Coriolis Effect influences the trajectory of many of these emission plumes, and have demonstrated how the additional curvature can lead to a substantial underestimation of the calculated emissions.
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