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Discussion papers
https://doi.org/10.5194/acp-2019-521
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2019-521
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 08 Jul 2019

Research article | 08 Jul 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

A methodology to constrain carbon dioxide emissions from coal-fired power plants using satellite observations of co-emitted nitrogen dioxide

Fei Liu1,2, Bryan N. Duncan2, Nickolay A. Krotkov2, Lok N. Lamsal1,2, Steffen Beirle3, Debora Griffin4, Chris A. McLinden4, Daniel L. Goldberg5, and Zifeng Lu5 Fei Liu et al.
  • 1Universities Space Research Association (USRA), Goddard Earth Sciences Technology and Research (GESTAR), Columbia, MD, USA
  • 2Goddard Space Flight Center, Greenbelt, MD, USA
  • 3Max-Planck-Institut für Chemie, Mainz, Germany
  • 4Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON, Canada
  • 5Energy Systems Division, Argonne National Laboratory, Lemont, IL, USA

Abstract. We present a novel method to infer CO2 emissions from individual power plants based on satellite observations of co-emitted nitrogen dioxide (NO2) and demonstrate its utility on US power plants, where accurate stack emission estimates of both gases are available for comparison. In the first step of our methodology, we infer nitrogen oxides (NOx) emissions from isolated power plants using Ozone Monitoring Instrument (OMI) NO2 tropospheric vertical column densities (VCDs) averaged over the ozone season (May–September) and a "top-down" approach that we previously developed. Second, we determine the relationship between NOx and CO2 emissions based on the direct stack emissions measurements reported by continuous emissions monitoring system (CEMS) programs, accounting for coal type, boiler firing type, NOx emission control device type, and changes in operating conditions. Third, we estimate CO2 emissions of the ozone season for a plant using the OMI-estimated NOx emissions and the CEMS NOx / CO2 emission ratio. We find that the CO2 emissions estimated by our satellite-based method during 2005–2017 are in reasonable agreement with the CEMS measurements, with a relative difference of 8 % ± 41 % (mean ± standard deviation) for the selected US power plants in our analysis. Total uncertainty in the inferred CO2 estimates is partly associated with the uncertainty associated with the OMI NO2 VCD data, so we expect that it will decrease when our method is applied to OMI-like sensors with improved capabilities, such as TROPOspheric Monitoring Instrument (TROPOMI) and geostationary Tropospheric Emissions: Monitoring Pollution (TEMPO). The broader implication of our methodology is that it has the potential to provide an additional constraint on CO2 emissions from power plants in regions of the world without reliable emissions accounting. We explore the feasibility by applying our methodology to a power plant in South Africa, where the satellite-based emission estimates show reasonable consistency with other estimates.

Fei Liu et al.
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Short summary
We present a novel method to infer CO2 emissions from individual power plants based on satellite observations of co-emitted NO2. We find that the CO2 emissions estimated by our satellite-based method during 2005–2017 are in reasonable agreement with the CEMS measurements for US power plants. The broader implication of our methodology is that it has the potential to provide an additional constraint on CO2 emissions from power plants in regions of the world without reliable emissions accounting.
We present a novel method to infer CO2 emissions from individual power plants based on satellite...
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