Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa

Janne Hakkarainen; Gerrit Kuhlmann; Erik Koene; Diego Santaren; Sandro Meier; Maarten C. Krol; Bart J.H. van Stratum; Iolanda Ialongo; Frédéric Chevallier; Johanna Tamminen; Dominik Brunner; Grégoire Broquet

doi:10.1016/j.apr.2024.102171

Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa

Janne Hakkarainen^*
, Gerrit Kuhlmann
, Erik Koene
, Diego Santaren
, Sandro Meier
, Maarten C. Krol
, Bart J.H. van Stratum
, Iolanda Ialongo
, Frédéric Chevallier
, Johanna Tamminen
, Dominik Brunner
, Grégoire Broquet

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

In this paper, we propose improved nitrogen dioxide (NO₂) to nitrogen oxide (NO_x) scaling factors for several data-driven methods that are used for the estimation of NO_x power plant emissions from satellite observations of NO₂. The scaling factors are deduced from high-resolution simulations of power plant plumes with the MicroHH large-eddy simulation model with a simplified chemistry and then applied to Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) NO₂ satellite observations over the Matimba/Medupi power stations in South Africa. We show that due to the non-linear chemistry the optimal NO₂ to NO_x scaling factors depend on both the method employed and the specific segments of the plume from which emission estimate is derived. The scaling factors derived from the MicroHH simulations in this study are substantially (more than 50%) higher than the typical values used in the literature with actual NO₂ observations. The results highlight the challenge in appropriately accounting for the conversion from NO₂ to NO_x when estimating point source emissions from satellite NO₂ observations.

Original language	English
Article number	102171
Number of pages	11
Journal	Atmospheric Pollution Research
Volume	15
Issue number	7
DOIs	https://doi.org/10.1016/j.apr.2024.102171
Publication status	Published - Jul 2024

Bibliographical note

Publisher Copyright:
© 2024 Turkish National Committee for Air Pollution Research and Control

Funding

Most of the work performed in this paper was done in the framework of EU H2020 project CoCO2 (Grant No. 958927). The FMI team also acknowledge additional funding from the Research Council of Finland (Grant Numbers 353082, 357904, 359196, 359455 and 331829). The Copernicus Sentinel-5P/TROPOMI data used in this work are provided as part of the Sentinel-5P Product Algorithm Laboratory (S5P-PAL).

Funders	Funder number
Research Council of Finland	353082, 359455, 331829, 357904, 359196
Horizon 2020 Framework Programme	958927

Keywords

Emission estimation
MicroHH
Nitrogen dioxide
Nitrogen oxides
Plume inversion
Power station
Satellite data
Sentinel-5P
TROPOMI

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10.1016/j.apr.2024.102171Licence: CC BY

1-s2.0-S1309104224001363-mainFinal published version, 2.38 MBLicence: CC BY

Cite this

Hakkarainen, J., Kuhlmann, G., Koene, E., Santaren, D., Meier, S., Krol, M. C., van Stratum, B. J. H., Ialongo, I., Chevallier, F., Tamminen, J., Brunner, D., & Broquet, G. (2024). Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa. Atmospheric Pollution Research, 15(7), Article 102171. https://doi.org/10.1016/j.apr.2024.102171

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title = "Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa",

abstract = "In this paper, we propose improved nitrogen dioxide (NO2) to nitrogen oxide (NOx) scaling factors for several data-driven methods that are used for the estimation of NOx power plant emissions from satellite observations of NO2. The scaling factors are deduced from high-resolution simulations of power plant plumes with the MicroHH large-eddy simulation model with a simplified chemistry and then applied to Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) NO2 satellite observations over the Matimba/Medupi power stations in South Africa. We show that due to the non-linear chemistry the optimal NO2 to NOx scaling factors depend on both the method employed and the specific segments of the plume from which emission estimate is derived. The scaling factors derived from the MicroHH simulations in this study are substantially (more than 50\%) higher than the typical values used in the literature with actual NO2 observations. The results highlight the challenge in appropriately accounting for the conversion from NO2 to NOx when estimating point source emissions from satellite NO2 observations.",

keywords = "Emission estimation, MicroHH, Nitrogen dioxide, Nitrogen oxides, Plume inversion, Power station, Satellite data, Sentinel-5P, TROPOMI",

author = "Janne Hakkarainen and Gerrit Kuhlmann and Erik Koene and Diego Santaren and Sandro Meier and Krol, \{Maarten C.\} and \{van Stratum\}, \{Bart J.H.\} and Iolanda Ialongo and Fr{\'e}d{\'e}ric Chevallier and Johanna Tamminen and Dominik Brunner and Gr{\'e}goire Broquet",

note = "Publisher Copyright: {\textcopyright} 2024 Turkish National Committee for Air Pollution Research and Control",

year = "2024",

month = jul,

doi = "10.1016/j.apr.2024.102171",

language = "English",

volume = "15",

journal = "Atmospheric Pollution Research",

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Hakkarainen, J, Kuhlmann, G, Koene, E, Santaren, D, Meier, S, Krol, MC, van Stratum, BJH, Ialongo, I, Chevallier, F, Tamminen, J, Brunner, D & Broquet, G 2024, 'Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa', Atmospheric Pollution Research, vol. 15, no. 7, 102171. https://doi.org/10.1016/j.apr.2024.102171

Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa. / Hakkarainen, Janne; Kuhlmann, Gerrit; Koene, Erik et al.
In: Atmospheric Pollution Research, Vol. 15, No. 7, 102171, 07.2024.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

T1 - Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods

T2 - A case study of Matimba/Medupi power stations in South Africa

AU - Hakkarainen, Janne

AU - Kuhlmann, Gerrit

AU - Koene, Erik

AU - Santaren, Diego

AU - Meier, Sandro

AU - Krol, Maarten C.

AU - van Stratum, Bart J.H.

AU - Ialongo, Iolanda

AU - Chevallier, Frédéric

AU - Tamminen, Johanna

AU - Brunner, Dominik

AU - Broquet, Grégoire

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N2 - In this paper, we propose improved nitrogen dioxide (NO2) to nitrogen oxide (NOx) scaling factors for several data-driven methods that are used for the estimation of NOx power plant emissions from satellite observations of NO2. The scaling factors are deduced from high-resolution simulations of power plant plumes with the MicroHH large-eddy simulation model with a simplified chemistry and then applied to Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) NO2 satellite observations over the Matimba/Medupi power stations in South Africa. We show that due to the non-linear chemistry the optimal NO2 to NOx scaling factors depend on both the method employed and the specific segments of the plume from which emission estimate is derived. The scaling factors derived from the MicroHH simulations in this study are substantially (more than 50%) higher than the typical values used in the literature with actual NO2 observations. The results highlight the challenge in appropriately accounting for the conversion from NO2 to NOx when estimating point source emissions from satellite NO2 observations.

AB - In this paper, we propose improved nitrogen dioxide (NO2) to nitrogen oxide (NOx) scaling factors for several data-driven methods that are used for the estimation of NOx power plant emissions from satellite observations of NO2. The scaling factors are deduced from high-resolution simulations of power plant plumes with the MicroHH large-eddy simulation model with a simplified chemistry and then applied to Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) NO2 satellite observations over the Matimba/Medupi power stations in South Africa. We show that due to the non-linear chemistry the optimal NO2 to NOx scaling factors depend on both the method employed and the specific segments of the plume from which emission estimate is derived. The scaling factors derived from the MicroHH simulations in this study are substantially (more than 50%) higher than the typical values used in the literature with actual NO2 observations. The results highlight the challenge in appropriately accounting for the conversion from NO2 to NOx when estimating point source emissions from satellite NO2 observations.

KW - Emission estimation

KW - MicroHH

KW - Nitrogen dioxide

KW - Nitrogen oxides

KW - Plume inversion

KW - Power station

KW - Satellite data

KW - Sentinel-5P

KW - TROPOMI

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DO - 10.1016/j.apr.2024.102171

M3 - Article

AN - SCOPUS:85191871532

SN - 1309-1042

VL - 15

JO - Atmospheric Pollution Research

JF - Atmospheric Pollution Research

IS - 7

M1 - 102171

ER -

Analyzing nitrogen dioxide to nitrogen oxide scaling factors for data-driven satellite-based emission estimation methods: A case study of Matimba/Medupi power stations in South Africa

Abstract

Bibliographical note

Funding

Keywords

Access to Document

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