Articles | Volume 18, issue 3
https://doi.org/10.5194/gmd-18-621-2025
https://doi.org/10.5194/gmd-18-621-2025
Model evaluation paper
 | 
05 Feb 2025
Model evaluation paper |  | 05 Feb 2025

Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes

Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma

Related authors

Monitoring of total and off-road NOx emissions from Canadian oil sands surface mining using the Ozone Monitoring Instrument
Chris A. McLinden, Debora Griffin, Vitali Fioletov, Junhua Zhang, Enrico Dammers, Cristen Adams, Mallory Loria, Nickolay Krotkov, and Lok N. Lamsal
Atmos. Chem. Phys., 25, 6093–6120, https://doi.org/10.5194/acp-25-6093-2025,https://doi.org/10.5194/acp-25-6093-2025, 2025
Short summary
Assessing the ability to quantify the decrease in NOx anthropogenic emissions in 2019 compared to 2005 using OMI and TROPOMI satellite observations
Audrey Fortems-Cheiney, Grégoire Broquet, Elise Potier, Antoine Berchet, Isabelle Pison, Adrien Martinez, Robin Plauchu, Rimal Abeed, Aurélien Sicsik-Paré, Gaelle Dufour, Adriana Coman, Dilek Savas, Guillaume Siour, Henk Eskes, Hugo A. C. Denier van der Gon, and Stijn N. C. Dellaert
Atmos. Chem. Phys., 25, 6047–6068, https://doi.org/10.5194/acp-25-6047-2025,https://doi.org/10.5194/acp-25-6047-2025, 2025
Short summary
Validation and uncertainty quantification of three state-of-the-art ammonia surface exchange schemes using NH3 flux measurements in a dune ecosystem
Tycho Jongenelen, Margreet van Zanten, Enrico Dammers, Roy Wichink Kruit, Arjan Hensen, Leon Geers, and Jan Willem Erisman
Atmos. Chem. Phys., 25, 4943–4963, https://doi.org/10.5194/acp-25-4943-2025,https://doi.org/10.5194/acp-25-4943-2025, 2025
Short summary
Improved consistency in solar-induced fluorescence retrievals from GOME-2A with the SIFTER v3 algorithm
Juliëtte C. S. Anema, K. Folkert Boersma, Lieuwe G. Tilstra, Olaf N. E. Tuinder, and Willem W. Verstraeten
Atmos. Meas. Tech., 18, 1961–1979, https://doi.org/10.5194/amt-18-1961-2025,https://doi.org/10.5194/amt-18-1961-2025, 2025
Short summary
Modelling stratospheric composition for the Copernicus Atmosphere Monitoring Service: multi-species evaluation of IFS-COMPO Cy49R1
Simon Chabrillat, Samuel Rémy, Quentin Errera, Vincent Huijnen, Christine Bingen, Jonas Debosscher, François Hendrick, Swen Metzger, Adrien Mora, Daniele Minganti, Marc Op de beek, Léa Reisenfeld, Jason E. Williams, Henk Eskes, and Johannes Flemming
EGUsphere, https://doi.org/10.5194/egusphere-2025-1327,https://doi.org/10.5194/egusphere-2025-1327, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary

Related subject area

Atmospheric sciences
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025,https://doi.org/10.5194/gmd-18-3707-2025, 2025
Short summary
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025,https://doi.org/10.5194/gmd-18-3681-2025, 2025
Short summary
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025,https://doi.org/10.5194/gmd-18-3623-2025, 2025
Short summary
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025,https://doi.org/10.5194/gmd-18-3607-2025, 2025
Short summary
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025,https://doi.org/10.5194/gmd-18-3559-2025, 2025
Short summary

Cited articles

Allen, D., Pickering, K. E., Bucsela, E., Geffen, J. V., Lapierre, J., Koshak, W., and Eskes, H.: Observations of Lightning NOx Production From Tropospheric Monitoring Instrument Case Studies Over the United States, J. Geophys. Res.-Atmos., 126, e2020JD034174, https://doi.org/10.1029/2020JD034174, 2021. a
Beirle, S., Platt, U., Wenig, M., and Wagner, T.: Weekly cycle of NO2 by GOME measurements: a signature of anthropogenic sources, Atmos. Chem. Phys., 3, 2225–2232, https://doi.org/10.5194/acp-3-2225-2003, 2003. a
Beirle, S., Boersma, K. F., Platt, U., Lawrence, M. G., and Wagner, T.: Megacity Emissions and Lifetimes of Nitrogen Oxides Probed from Space, Science, 333, 1737–1739, https://doi.org/10.1126/science.1207824, 2011. a
Beirle, S., Borger, C., Dörner, S., Li, A., Hu, Z., Liu, F., Wang, Y., and Wagner, T.: Pinpointing nitrogen oxide emissions from space, Science Advances, 5, eaax9800, https://doi.org/10.1126/SCIADV.AAX9800, 2019. a, b, c, d, e, f, g, h
Beirle, S., Borger, C., Dörner, S., Eskes, H., Kumar, V., de Laat, A., and Wagner, T.: Catalog of NOx emissions from point sources as derived from the divergence of the NO2 flux for TROPOMI, Earth Syst. Sci. Data, 13, 2995–3012, https://doi.org/10.5194/essd-13-2995-2021, 2021. a, b, c, d
Download
Short summary
We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NO: NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Share