Articles | Volume 12, issue 12
https://doi.org/10.5194/amt-12-6695-2019
https://doi.org/10.5194/amt-12-6695-2019
Research article
 | 
19 Dec 2019
Research article |  | 19 Dec 2019

Detectability of CO2 emission plumes of cities and power plants with the Copernicus Anthropogenic CO2 Monitoring (CO2M) mission

Gerrit Kuhlmann, Grégoire Broquet, Julia Marshall, Valentin Clément, Armin Löscher, Yasjka Meijer, and Dominik Brunner

Related authors

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. Discuss., https://doi.org/10.5194/gmd-2024-156,https://doi.org/10.5194/gmd-2024-156, 2024
Preprint under review for GMD
Short summary
A lightweight NO2-to-NOx conversion model for quantifying NOx emissions of point sources from NO2 satellite observations
Sandro Meier, Erik F. M. Koene, Maarten Krol, Dominik Brunner, Alexander Damm, and Gerrit Kuhlmann
Atmos. Chem. Phys., 24, 7667–7686, https://doi.org/10.5194/acp-24-7667-2024,https://doi.org/10.5194/acp-24-7667-2024, 2024
Short summary
The ddeq Python library for point source quantification from remote sensing images (version 1.0)
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024,https://doi.org/10.5194/gmd-17-4773-2024, 2024
Short summary
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024,https://doi.org/10.5194/gmd-17-1995-2024, 2024
Short summary
Benchmarking data-driven inversion methods for the estimation of local CO2 emissions from XCO2 and NO2 satellite images
Diego Santaren, Janne Hakkarainen, Gerrit Kuhlmann, Erik Koene, Frédéric Chevallier, Iolanda Ialongo, Hannakaisa Lindqvist, Janne Nurmela, Johanna Tamminen, Laia Amoros, Dominik Brunner, and Grégoire Broquet
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-241,https://doi.org/10.5194/amt-2023-241, 2024
Revised manuscript accepted for AMT
Short summary

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Improved convective cloud differential (CCD) tropospheric ozone from S5P-TROPOMI satellite data using local cloud fields
Swathi Maratt Satheesan, Kai-Uwe Eichmann, John P. Burrows, Mark Weber, Ryan Stauffer, Anne M. Thompson, and Debra Kollonige
Atmos. Meas. Tech., 17, 6459–6484, https://doi.org/10.5194/amt-17-6459-2024,https://doi.org/10.5194/amt-17-6459-2024, 2024
Short summary
Atmospheric propane (C3H8) column retrievals from ground-based FTIR observations in Xianghe, China
Minqiang Zhou, Pucai Wang, Bart Dils, Bavo Langerock, Geoff Toon, Christian Hermans, Weidong Nan, Qun Cheng, and Martine De Mazière
Atmos. Meas. Tech., 17, 6385–6396, https://doi.org/10.5194/amt-17-6385-2024,https://doi.org/10.5194/amt-17-6385-2024, 2024
Short summary
Can the remote sensing of combustion phase improve estimates of landscape fire smoke emission rate and composition?
Farrer Owsley-Brown, Martin J. Wooster, Mark J. Grosvenor, and Yanan Liu
Atmos. Meas. Tech., 17, 6247–6264, https://doi.org/10.5194/amt-17-6247-2024,https://doi.org/10.5194/amt-17-6247-2024, 2024
Short summary
Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS
Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Víctor Molina García, Diego Loyola, Hanlim Lee, and Jhoon Kim
Atmos. Meas. Tech., 17, 6163–6191, https://doi.org/10.5194/amt-17-6163-2024,https://doi.org/10.5194/amt-17-6163-2024, 2024
Short summary
Troposphere–stratosphere-integrated bromine monoxide (BrO) profile retrieval over the central Pacific Ocean
Theodore K. Koenig, François Hendrick, Douglas Kinnison, Christopher F. Lee, Michel Van Roozendael, and Rainer Volkamer
Atmos. Meas. Tech., 17, 5911–5934, https://doi.org/10.5194/amt-17-5911-2024,https://doi.org/10.5194/amt-17-5911-2024, 2024
Short summary

Cited articles

Ackerman, S., Holz, R., Frey, R., Eloranta, E., Maddux, B., and McGill, M.: Cloud detection with MODIS. Part II: validation, J. Atmos. Ocean. Tech., 25, 1073–1086, https://doi.org/10.1175/2007JTECHA1053.1, 2008. a
Ackerman, S., Menzel, P., Frey R., and Baum, B.: MODIS Atmosphere L2 Cloud Mask Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, https://doi.org/10.5067/MODIS/MYD35_L2.061, 2017. a
Agustí-Panareda, A., Massart, S., Chevallier, F., Boussetta, S., Balsamo, G., Beljaars, A., Ciais, P., Deutscher, N. M., Engelen, R., Jones, L., Kivi, R., Paris, J.-D., Peuch, V.-H., Sherlock, V., Vermeulen, A. T., Wennberg, P. O., and Wunch, D.: Forecasting global atmospheric CO2, Atmos. Chem. Phys., 14, 11959–11983, https://doi.org/10.5194/acp-14-11959-2014, 2014. a
AVISO GmbH and IE Leipzig: Erstellung der Berliner Emissionskataster Industrie, Gebäudeheizung, sonstiger Verkehr, Kleingewerbe, sonstige Quellen, Baustellen – Schlussbericht Juni 2016, Tech. rep., available at: https://www.berlin.de/senuvk/umwelt/luftqualitaet/de/emissionen/download/Endbericht_Emissionkataster_2015.pdf (last access: 25 November 2019), 2016. a
Bacour, C., Boesch, H., Bovensmann, H., Breon, F.-M., Broquet, G., Buchwitz, M., Houweling, S., Klonecki, A., Krings, T., and Santaren, D.: LOGOFLUX 2 – CarbonSat Earth Explorer 8 Candidate Mission – Inverse Modelling and Mission Performance Study, Final report of ESA study contract n°4000109818/14/NL/FF/lf, project led by NOVELTIS (France), Report, 2015. a, b, c
Short summary
The Copernicus Anthropogenic CO2 Monitoring (CO2M) mission is a proposed constellation of imaging satellites with a CO2 instrument as main payload and optionally instruments for NO2, CO and aerosols. This study demonstrates the huge benefit of an NO2 instrument for detecting city plumes and weak point sources. Its main advantages are the higher signal-to-noise ratio and the lower sensitivity to clouds that significantly increases the number of observations available for quantifying CO2 emission.