Articles | Volume 13, issue 12
https://doi.org/10.5194/amt-13-6733-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-6733-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
15 Dec 2020
Research article | Highlight paper |
| 15 Dec 2020
| 15 Dec 2020
Quantifying CO2 emissions of a city with the Copernicus Anthropogenic CO2 Monitoring satellite mission
Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
Grégoire Broquet
Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Yasjka Meijer
European Space Agency (ESA), ESTEC, Noordwijk, the Netherlands
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Short summary
Monitoring of CO2 emissions is key to the development of reduction policies. Local emissions, from cities or power plants, may be estimated from CO2 plumes detected in satellite images. CO2 plumes generally have a weak signal and are partially concealed by highly variable background concentrations and instrument errors, which hampers their detection. To address this problem, we propose and apply deep learning methods to detect the contour of a plume in simulated CO2 satellite images.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Dominik Brunner, Gerrit Kuhlmann, Stephan Henne, Erik Koene, Bastian Kern, Sebastian Wolff, Christiane Voigt, Patrick Jöckel, Christoph Kiemle, Anke Roiger, Alina Fiehn, Sven Krautwurst, Konstantin Gerilowski, Heinrich Bovensmann, Jakob Borchardt, Michal Galkowski, Christoph Gerbig, Julia Marshall, Andrzej Klonecki, Pascal Prunet, Robert Hanfland, Margit Pattantyús-Ábrahám, Andrzej Wyszogrodzki, and Andreas Fix
Atmos. Chem. Phys., 23, 2699–2728, https://doi.org/10.5194/acp-23-2699-2023, https://doi.org/10.5194/acp-23-2699-2023, 2023
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We evaluated six atmospheric transport models for their capability to simulate the CO2 plumes from two of the largest power plants in Europe by comparing the models against aircraft observations collected during the CoMet (Carbon Dioxide and Methane Mission) campaign in 2018. The study analyzed how realistically such plumes can be simulated at different model resolutions and how well the planned European satellite mission CO2M will be able to quantify emissions from power plants.
Prabhakar Shrestha, Jana Mendrok, and Dominik Brunner
Atmos. Chem. Phys., 22, 14095–14117, https://doi.org/10.5194/acp-22-14095-2022, https://doi.org/10.5194/acp-22-14095-2022, 2022
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The study extends the Terrestrial Systems Modeling Platform with gas-phase chemistry aerosol dynamics and a radar forward operator to enable detailed studies of aerosol–cloud–precipitation interactions. This is demonstrated using a case study of a deep convective storm, which showed that the strong updraft in the convective core of the storm produced aerosol-tower-like features, which affected the size of the hydrometeors and the simulated polarimetric features (e.g., ZDR and KDP columns).
Peter Bergamaschi, Arjo Segers, Dominik Brunner, Jean-Matthieu Haussaire, Stephan Henne, Michel Ramonet, Tim Arnold, Tobias Biermann, Huilin Chen, Sebastien Conil, Marc Delmotte, Grant Forster, Arnoud Frumau, Dagmar Kubistin, Xin Lan, Markus Leuenberger, Matthias Lindauer, Morgan Lopez, Giovanni Manca, Jennifer Müller-Williams, Simon O'Doherty, Bert Scheeren, Martin Steinbacher, Pamela Trisolino, Gabriela Vítková, and Camille Yver Kwok
Atmos. Chem. Phys., 22, 13243–13268, https://doi.org/10.5194/acp-22-13243-2022, https://doi.org/10.5194/acp-22-13243-2022, 2022
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We present a novel high-resolution inverse modelling system, "FLEXVAR", and its application for the inverse modelling of European CH4 emissions in 2018. The new system combines a high spatial resolution of 7 km x 7 km with a variational data assimilation technique, which allows CH4 emissions to be optimized from individual model grid cells. The high resolution allows the observations to be better reproduced, while the derived emissions show overall good consistency with two existing models.
Simone M. Pieber, Béla Tuzson, Stephan Henne, Ute Karstens, Christoph Gerbig, Frank-Thomas Koch, Dominik Brunner, Martin Steinbacher, and Lukas Emmenegger
Atmos. Chem. Phys., 22, 10721–10749, https://doi.org/10.5194/acp-22-10721-2022, https://doi.org/10.5194/acp-22-10721-2022, 2022
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Understanding regional greenhouse gas emissions into the atmosphere is a prerequisite to mitigate climate change. In this study, we investigated the regional contributions of carbon dioxide (CO2) at the location of the high Alpine observatory Jungfraujoch (JFJ, Switzerland, 3580 m a.s.l.). To this purpose, we combined receptor-oriented atmospheric transport simulations for CO2 concentration in the period 2009–2017 with stable carbon isotope (δ13C–CO2) information.
Randulph Morales, Jonas Ravelid, Katarina Vinkovic, Piotr Korbeń, Béla Tuzson, Lukas Emmenegger, Huilin Chen, Martina Schmidt, Sebastian Humbel, and Dominik Brunner
Atmos. Meas. Tech., 15, 2177–2198, https://doi.org/10.5194/amt-15-2177-2022, https://doi.org/10.5194/amt-15-2177-2022, 2022
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Mapping trace gas emission plumes using in situ measurements from unmanned aerial vehicles (UAVs) is an emerging and attractive possibility to quantify emissions from localized sources. We performed an extensive controlled-release experiment to develop an optimal quantification method and to determine the related uncertainties under various environmental and sampling conditions. Our approach was successful in quantifying local methane sources from drone-based measurements.
Gerrit Kuhlmann, Ka Lok Chan, Sebastian Donner, Ying Zhu, Marc Schwaerzel, Steffen Dörner, Jia Chen, Andreas Hueni, Duc Hai Nguyen, Alexander Damm, Annette Schütt, Florian Dietrich, Dominik Brunner, Cheng Liu, Brigitte Buchmann, Thomas Wagner, and Mark Wenig
Atmos. Meas. Tech., 15, 1609–1629, https://doi.org/10.5194/amt-15-1609-2022, https://doi.org/10.5194/amt-15-1609-2022, 2022
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Nitrogen dioxide (NO2) is an air pollutant whose concentration often exceeds air quality guideline values, especially in urban areas. To map the spatial distribution of NO2 in Munich, we conducted the Munich NO2 Imaging Campaign (MuNIC), where NO2 was measured with stationary, mobile, and airborne in situ and remote sensing instruments. The campaign provides a unique dataset that has been used to compare the different instruments and to study the spatial variability of NO2 and its sources.
Marc Schwaerzel, Dominik Brunner, Fabian Jakub, Claudia Emde, Brigitte Buchmann, Alexis Berne, and Gerrit Kuhlmann
Atmos. Meas. Tech., 14, 6469–6482, https://doi.org/10.5194/amt-14-6469-2021, https://doi.org/10.5194/amt-14-6469-2021, 2021
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NO2 maps from airborne imaging remote sensing often appear much smoother than one would expect from high-resolution model simulations of NO2 over cities, despite the small ground-pixel size of the sensors. Our case study over Zurich, using the newly implemented building module of the MYSTIC radiative transfer solver, shows that the 3D effect can explain part of the smearing and that building shadows cause a noticeable underestimation and noise in the measured NO2 columns.
Antoine Berchet, Espen Sollum, Rona L. Thompson, Isabelle Pison, Joël Thanwerdas, Grégoire Broquet, Frédéric Chevallier, Tuula Aalto, Adrien Berchet, Peter Bergamaschi, Dominik Brunner, Richard Engelen, Audrey Fortems-Cheiney, Christoph Gerbig, Christine D. Groot Zwaaftink, Jean-Matthieu Haussaire, Stephan Henne, Sander Houweling, Ute Karstens, Werner L. Kutsch, Ingrid T. Luijkx, Guillaume Monteil, Paul I. Palmer, Jacob C. A. van Peet, Wouter Peters, Philippe Peylin, Elise Potier, Christian Rödenbeck, Marielle Saunois, Marko Scholze, Aki Tsuruta, and Yuanhong Zhao
Geosci. Model Dev., 14, 5331–5354, https://doi.org/10.5194/gmd-14-5331-2021, https://doi.org/10.5194/gmd-14-5331-2021, 2021
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We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is a programming protocol to allow various inversion bricks to be exchanged among researchers.
The ensemble of bricks makes a flexible, transparent and open-source Python-based tool. We describe the main structure and functionalities and demonstrate it in a simple academic case.
Ana Maria Roxana Petrescu, Chunjing Qiu, Philippe Ciais, Rona L. Thompson, Philippe Peylin, Matthew J. McGrath, Efisio Solazzo, Greet Janssens-Maenhout, Francesco N. Tubiello, Peter Bergamaschi, Dominik Brunner, Glen P. Peters, Lena Höglund-Isaksson, Pierre Regnier, Ronny Lauerwald, David Bastviken, Aki Tsuruta, Wilfried Winiwarter, Prabir K. Patra, Matthias Kuhnert, Gabriel D. Oreggioni, Monica Crippa, Marielle Saunois, Lucia Perugini, Tiina Markkanen, Tuula Aalto, Christine D. Groot Zwaaftink, Hanqin Tian, Yuanzhi Yao, Chris Wilson, Giulia Conchedda, Dirk Günther, Adrian Leip, Pete Smith, Jean-Matthieu Haussaire, Antti Leppänen, Alistair J. Manning, Joe McNorton, Patrick Brockmann, and Albertus Johannes Dolman
Earth Syst. Sci. Data, 13, 2307–2362, https://doi.org/10.5194/essd-13-2307-2021, https://doi.org/10.5194/essd-13-2307-2021, 2021
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This study is topical and provides a state-of-the-art scientific overview of data availability from bottom-up and top-down CH4 and N2O emissions in the EU27 and UK. The data integrate recent emission inventories with process-based model data and regional/global inversions for the European domain, aiming at reconciling them with official country-level UNFCCC national GHG inventories in support to policy and to facilitate real-time verification procedures.
Stephanie P. Rusli, Otto Hasekamp, Joost aan de Brugh, Guangliang Fu, Yasjka Meijer, and Jochen Landgraf
Atmos. Meas. Tech., 14, 1167–1190, https://doi.org/10.5194/amt-14-1167-2021, https://doi.org/10.5194/amt-14-1167-2021, 2021
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This study investigates the added value of multi-angle polarimeter (MAP) measurements for XCO2 retrievals, particularly in the context of the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission. In this paper, we derive the required MAP instrument specification, and we demonstrate that MAP observations significantly improve the retrieval performance and are needed to meet the XCO2 precision and accuracy requirements of the CO2M mission.
Yilong Wang, Grégoire Broquet, François-Marie Bréon, Franck Lespinas, Michael Buchwitz, Maximilian Reuter, Yasjka Meijer, Armin Loescher, Greet Janssens-Maenhout, Bo Zheng, and Philippe Ciais
Geosci. Model Dev., 13, 5813–5831, https://doi.org/10.5194/gmd-13-5813-2020, https://doi.org/10.5194/gmd-13-5813-2020, 2020
Ying Zhu, Jia Chen, Xiao Bi, Gerrit Kuhlmann, Ka Lok Chan, Florian Dietrich, Dominik Brunner, Sheng Ye, and Mark Wenig
Atmos. Chem. Phys., 20, 13241–13251, https://doi.org/10.5194/acp-20-13241-2020, https://doi.org/10.5194/acp-20-13241-2020, 2020
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Average NO2 concentration of on-street mobile measurements (MMs) near the monitoring stations (MSs) was found to be considerably higher than the MSs data. The common measurement height (H) and distance (D) of the MSs result in 27 % lower average concentrations in total than the concentration of our MMs. Another 21 % difference remained after correcting the influence of the measuring H and D. This result makes our city-wide measurements for capturing the full range of concentrations necessary.
Cited articles
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
Allen, D. R., Hoppel, K. W., Nedoluha, G. E., Kuhl, D. D., Baker, N. L., Xu, L., and Rosmond,
T. E.: Limitations of wind extraction from 4D-Var assimilation of ozone, Atmos. Chem. Phys., 13,
3501–3515, https://doi.org/10.5194/acp-13-3501-2013, 2013. 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: 30 November 2020), 2016. a, b
Baldauf, M., Seifert, A., Forstner, J., Majewski, D., Raschendorfer,
M., and Reinhardt, T.: Operational convective-scale numerical weather prediction with the COSMO
model: description and sensitivities, Mon. Weather Rev., 139, 3887–3905,
https://doi.org/10.1175/Mwr-D-10-05013.1, 2011. 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, b
Beirle, S., Borger, C., Dörner, S., Li, A., Hu, Z., Liu, F., Wang, Y., and Wagner, T.: Pinpointing nitrogen oxide emissions from space, Sci. Adv., 5, eaax9800, https://doi.org/10.1126/sciadv.aax9800, 2019. a
Boersma, K. F.,
Eskes, H. J., Dirksen, R. J., van der A, R. J., V Boersma, K. F., Eskes, H. J., Dirksen, R. J.,
van der A, R. J., Veefkind, J. P., Stammes, P., Huijnen, V., Kleipool, Q. L., Sneep, M., Claas,
J., Leitão, J., Richter, A., Zhou, Y., and Brunner, D.: An improved tropospheric NO2
column retrieval algorithm for the Ozone Monitoring Instrument, Atmos. Meas. Tech., 4, 1905–1928,
https://doi.org/10.5194/amt-4-1905-2011, 2011. a
Bovensmann, H., Buchwitz, M.,
Burrows, J. P., Reuter, M., Krings, T., Gerilowski, K., Schneising, O., Heymann, J., Tretner, A.,
and Erzinger, J.: A remote sensing technique for global monitoring of power plant CO2
emissions from space and related applications, Atmos. Meas. Tech., 3, 781–811,
https://doi.org/10.5194/amt-3-781-2010, 2010. a
Broquet, G., Bréon, F.-M., Renault, E., Buchwitz, M., Reuter,
M., Bovensmann, H., Chevallier, F., Wu, L., and Ciais, P.: The potential of satellite
spectro-imagery for monitoring CO2 emissions from large cities, Atmos. Meas. Tech., 11,
681–708, https://doi.org/10.5194/amt-11-681-2018, 2018. a, b, c, d
Brunner, D., Kuhlmann, G., Marshall, J., Clément, V., Fuhrer, O.,
Broquet, G., Löscher, A., and Meijer, Y.: Accounting for the vertical distribution of
emissions in atmospheric CO2 simulations, Atmos. Chem. Phys., 19, 4541–4559,
https://doi.org/10.5194/acp-19-4541-2019, 2019. a, b, c
Buchwitz, M., Reuter, M.,
Bovensmann, H., Pillai, D., Heymann, J., Schneising, O., Rozanov, V., Krings, T., Burrows, J. P.,
Boesch, H., Gerbig, C., Meijer, Y., and Löscher, A.: Carbon Monitoring Satellite (CarbonSat):
assessment of atmospheric CO2 and CH4 retrieval errors by error parameterization,
Atmos. Meas. Tech., 6, 3477–3500, https://doi.org/10.5194/amt-6-3477-2013, 2013. a
C40 cities: 27 Cities Have Reached Peak Greenhouse Gas Emissions whilst Populations Increase and Economies Grow, Press release, available at: https://www.c40.org/press_releases/27-cities-have-reached-peak-greenhouse-gas-emissions-whilst-
-populations-increase-and-economies-grow (last access: 30 November 2020), 2018. a
Ciais, P., Crisp, D., v. d. Gon, H., Engelen, R., Heimann, M.,
Janssens-Maenhout, G., Rayner, P., and Scholze, M.: Towards a European Operational Observing
System to Monitor Fossil CO2 emissions – Final Report from the expert group, Copernicus
Climate Change Service, Report, European Commission, Brussels,
2015. a
Düring, I., Bächlin, W., Ketzel, M., Baum, A., Friedrich, U., and Wurzler, S.: A new simplified NO/NO2 conversion model under consideration of direct NO2-emissions, Meteorol. Z., 20, 67–73, https://doi.org/10.1127/0941-2948/2011/0491, 2011. a
Empa – Laboratory for Air Pollution/Environmental Technology – GitLab group “empa503”: https://gitlab.com/empa503, last access: 30 November 2020. a
ESA: Report for mission selection: CarbonSat, ESA SP-1330/1 (2 volume series), Report, ESA communications, Noordwijk, 2015. a
Fioletov, V. E.,
McLinden, C. A., Krotkov, N., and Li, C.: Lifetimes and emissions of SO2 from point
sources estimated from OMI, Geophys. Res. Lett., 42, 1969–1976, https://doi.org/10.1002/2015GL063148, 2015. a
Flemming, J., Huijnen, V., Arteta, J., Bechtold, P.,
Beljaars, A., Blechschmidt, A.-M., Diamantakis, M., Engelen, R. J., Gaudel, A., Inness, A., Jones,
L., Josse, B., Katragkou, E., Marecal, V., Peuch, V.-H., Richter, A., Schultz, M. G., Stein, O.,
and Tsikerdekis, A.: Tropospheric chemistry in the Integrated Forecasting System of ECMWF,
Geosci. Model Dev., 8, 975–1003, https://doi.org/10.5194/gmd-8-975-2015, 2015. a
Gately, C. K. and Hutyra, L. R.: Large Uncertainties
in Urban-Scale Carbon Emissions, J. Geophys. Res.-Atmos., 122, 11,242–11,260,
https://doi.org/10.1002/2017JD027359, 2017. a
Gurney, K. R., Patarasuk, R., Liang, J., Song, Y., O'Keeffe,
D., Rao, P., Whetstone, J. R., Duren, R. M., Eldering, A., and Miller, C.: The Hestia fossil fuel
CO2 emissions data product for the Los Angeles megacity (Hestia-LA), Earth
Syst. Sci. Data, 11, 1309–1335, https://doi.org/10.5194/essd-11-1309-2019, 2019. a
Houweling, S., Landgraf, J., van Heck, H., Vlemmix, T., and Tao, W.: AEROCARB – Study on use of aerosol information for estimating fossil CO2 emissions, Final report: Synthesis and Recommendation, Tech. rep., ESA study contract RFP/3-14860/17/NL/FF/gp, SRON – Netherlands Institute for Space Research
Location: Utrecht, 2019. a
International Energy Agency: Implications of the reference scenario for the global climate, World Energy Outlook, IEA, Paris, 381–406, available at:
https://www.iea.org/reports/world-energy-outlook-2008 (last access: 30 November 2020), 2008. a
Jähn, M., Kuhlmann, G., Mu, Q., Haussaire, J.-M., Ochsner, D.,
Osterried, K., Clément, V., and Brunner, D.: An online emission module for atmospheric
chemistry transport models: implementation in COSMO-GHG v5.6a and COSMO-ART v5.1-3.1,
Geosci. Model Dev., 13, 2379–2392, https://doi.org/10.5194/gmd-13-2379-2020, 2020. a
Janssens-Maenhout, G., Pinty, B., Dowell, M., Zunker, H., Andersson, E., Balsamo, G., Bézy, J.-L., Brunhes, T., Bösch, H., Bojkov, B., Brunner, D., Buchwitz, M., Crisp, D., Ciais, P., Counet, P., Dee, D., Denier van der Gon, H., Dolman, H., Drinkwater, M., Dubovik, O., Engelen, R., Fehr, T., Fernandez, V., Heimann, M., Holmlund, K., Houweling, S., Husband, R., Juvyns, O., Kentarchos, A., Landgraf, J., Lang, R., Löscher, A., Marshall, J., Meijer, Y., Nakajima, M., Palmer, P., Peylin, P., Rayner, P., Scholze, M., Sierk, B., Tamminen, J., and Veefkind, P.: Towards an operational anthropogenic CO2 emissions monitoring and verification support capacity, B. Am. Meteorol. Soc., 101, E1439–E1451, https://doi.org/10.1175/BAMS-D-19-0017.1, 2020. a
Klausner, T., Mertens, M., Huntrieser, H.,
Galkowski, M., Kuhlmann, G., Baumann, R., Fiehn, A., Jöckel, P., Pühl, M., and Roiger, A.:
Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO2 and
CH4 in situ observations in summer 2018, Elem. Sci. Anth., 8, 15,
https://doi.org/10.1525/elementa.411, 2019. a
Krings, T., Gerilowski, K., Buchwitz, M., Hartmann, J., Sachs, T.,
Erzinger, J., Burrows, J. P., and Bovensmann, H.: Quantification of methane emission rates from
coal mine ventilation shafts using airborne remote sensing data, Atmos. Meas. Tech., 6, 151–166,
https://doi.org/10.5194/amt-6-151-2013, 2013. a
Kuenen, J. J. P., Visschedijk, A. J. H., Jozwicka, M., and Denier van der Gon, H. A. C.:
TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European
emission inventory for air quality modelling, Atmos. Chem. Phys., 14, 10963–10976,
https://doi.org/10.5194/acp-14-10963-2014, 2014. a
Kuhlmann, G., Broquet, G., Marshall, J., Clément, V.,
Löscher, A., Meijer, Y., and Brunner, D.: Detectability of CO2 emission plumes of cities and
power plants with the Copernicus Anthropogenic CO2 Monitoring (CO2M) mission,
Atmos. Meas. Tech., 12, 6695–6719, https://doi.org/10.5194/amt-12-6695-2019, 2019a. a, b, c, d, e, f
Kuhlmann, G., Clément, V.,
Marschall, J., Fuhrer, O., Broquet, G., Schnadt-Poberaj, C., Löscher, A., Meijer, Y., and
Brunner, D.: SMARTCARB – Use of Satellite Measurements of Auxiliary Reactive Trace Gases for
Fossil Fuel Carbon Dioxide Emission Estimation, Final report of ESA study contract no
4000119599/16/NL/FF/mg, Tech. rep., Empa, Swiss Federal Laboratories for Materials Science and
Technology, Dübendorf, Switzerland, https://doi.org/10.5281/zenodo.4034266, 2019b. a
Kuhlmann, G., Clément, V., Marshall, J., Fuhrer, O., Broquet, G., Schnadt-Poberaj, C., Löscher, A., Meijer, Y., and Brunner, D.: Synthetic XCO2, CO and NO2 observations for the CO2M and Sentinel-5 satellites, Data set, Zenodo, https://doi.org/10.5281/zenodo.4048228, 2020. a
Laughner, J. L. and Cohen, R. C.: Direct
observation of changing NOx lifetime in North American cities, Science, 366,
723–727, https://doi.org/10.1126/science.aax6832, 2019. a
Liu, Y., Gruber, N., and Brunner, D.:
Spatiotemporal patterns of the fossil-fuel CO2 signal in central Europe: results from a
high-resolution atmospheric transport model, Atmos. Chem. Phys., 17, 14145–14169,
https://doi.org/10.5194/acp-17-14145-2017, 2017. a
Lorente, A., Boersma, K., Eskes, H., Veefkind, J., Van Geffen,
J., de Zeeuw, M., van der Gon, H. D., Beirle, S., and Krol, M.: Quantification of nitrogen oxides
emissions from build-up of pollution over Paris with TROPOMI, Sci. Rep.-UK, 9, 1–10,
https://doi.org/10.1038/s41598-019-56428-5, 2019. a
Mahadevan, P., Wofsy, S. C., Matross, D. M., Xiao, X., Dunn,
A. L., Lin, J. C., Gerbig, C., Munger, J. W., Chow, V. Y., and Gottlieb, E. W.: A satellite-based
biosphere parameterization for net ecosystem CO2 exchange: Vegetation Photosynthesis and
Respiration Model (VPRM), Global Biogeochem. Cy., 22, https://doi.org/10.1029/2006GB002735, 2008. a
Nassar, R., Napier-Linton, L., Gurney, K. R., Andres, R. J., Oda, T., Vogel,
F. R., and Deng, F.: Improving the temporal and spatial distribution of CO2 emissions
from global fossil fuel emission data sets, J. Geophys. Res.-Atmos., 118, 917–933,
https://doi.org/10.1029/2012JD018196, 2013. a
Nassar,
R., Hill, T. G., McLinden, C. A., Wunch, D., Jones, D. B. A., and Crisp, D.: Quantifying
CO2 Emissions From Individual Power Plants From Space, Geophys. Res. Lett., 44,
10045–10053, https://doi.org/10.1002/2017GL074702, 2017. a
Peylin, P.,
Houweling, S., Krol, M. C., Karstens, U., Rödenbeck, C., Geels, C., Vermeulen, A., Badawy, B.,
Aulagnier, C., Pregger, T., Delage, F., Pieterse, G., Ciais, P., and Heimann, M.: Importance of
fossil fuel emission uncertainties over Europe for CO2 modeling: model intercomparison,
Atmos. Chem. Phys., 11, 6607–6622, https://doi.org/10.5194/acp-11-6607-2011, 2011. a
Pillai, D., Buchwitz, M., Gerbig, C., Koch, T., Reuter, M., Bovensmann,
H., Marshall, J., and Burrows, J. P.: Tracking city CO2 emissions from space using a
high-resolution inverse modelling approach: a case study for Berlin, Germany, Atmos. Chem. Phys.,
16, 9591–9610, https://doi.org/10.5194/acp-16-9591-2016, 2016. a, b, c
Pinty, B., Janssens-Maenhout, G., Dowell, M., Zunker, H., Brunhe, T., Ciais, P., Dee, D., van der Gon, H. D., Dolman, H., Drinkwater, M., Engelen, R., Heimann, M., Holmlund, K., Husband, R., Kentarchos, A., Meijer, Y., Palmer, P., and Scholze, M.: An Operational Anthropogenic CO2 Emissions Monitoring & Verification Support capacity – Baseline Requirements, Model Components and Functional Architecture, Report, available at: https://www.copernicus.eu/sites/default/files/2019-09/CO2_Red_Report_2017.pdf (last access: 30 November 2020), 2017. a
Pitt, J. R., Allen, G., Bauguitte, S. J.-B., Gallagher, M. W., Lee, J. D.,
Drysdale, W., Nelson, B., Manning, A. J., and Palmer, P. I.: Assessing London CO2,
CH4 and CO emissions using aircraft measurements and dispersion modelling,
Atmos. Chem. Phys., 19, 8931–8945, https://doi.org/10.5194/acp-19-8931-2019, 2019. a
Reuter, M., Buchwitz, M., Schneising, O., Krautwurst, S., O'Dell,
C. W., Richter, A., Bovensmann, H., and Burrows, J. P.: Towards monitoring localized CO2
emissions from space: co-located regional CO2 and NO2 enhancements observed by the
OCO-2 and S5P satellites, Atmos. Chem. Phys., 19, 9371–9383, https://doi.org/10.5194/acp-19-9371-2019,
2019. a, b, c
Rockström, J., Gaffney, O., Rogelj, J., Meinshausen, M.,
Nakicenovic, N., and Schellnhuber, H. J.: A roadmap for rapid decarbonization, Science, 355,
1269–1271, https://doi.org/10.1126/science.aah3443, 2017. a
Sharp, E., Dodds, P.,
Barrett, M., and Spataru, C.: Evaluating the accuracy of CFSR reanalysis hourly wind speed
forecasts for the UK, using in situ measurements and geographical information, Renew. Energ., 77,
527–538, https://doi.org/10.1016/j.renene.2014.12.025, 2015. a
Sierk, B., Bézy, J.-L., Löscher, A., and Meijer, Y.: The European CO2 Monitoring Mission: observing anthropogenic greenhouse gas emissions from space, SPIE, 237–250, https://doi.org/10.1117/12.2535941, 2019. a, b
Super,
I., Dellaert, S. N. C., Visschedijk, A. J. H., and Denier van der Gon, H. A. C.: Uncertainty
analysis of a European high-resolution emission inventory of CO2 and CO to support inverse
modelling and network design, Atmos. Chem. Phys., 20, 1795–1816, https://doi.org/10.5194/acp-20-1795-2020,
2020. a, b
Turnbull, J. C., Karion, A., Davis, K. J., Lauvaux, T., Miles, N. L.,
Richardson, S. J., Sweeney, C., McKain, K., Lehman, S. J., Gurney, K. R.,
Patarasuk, R., Liang, J., Shepson, P. B., Heimburger, A., Harvey, R., and Whetstone, J.: Synthesis of Urban CO2 Emission Estimates from Multiple Methods from the Indianapolis Flux Project (INFLUX), Environ. Sci. Technol., 53, 287–295, 2018. a
United Nations: World Urbanization Prospects: The 2018 Revision, Department of Economic and Social Affairs, Population Division, online edn., available at: https://population.un.org/wup/ (last access: 30 November 2020), 2018. a
Wang, Y., Ciais, P., Broquet, G., Bréon, F.-M., Oda, T., Lespinas, F., Meijer, Y., Loescher, A., Janssens-Maenhout, G., Zheng, B., Xu, H., Tao, S., Gurney, K. R., Roest, G., Santaren, D., and Su, Y.: A global map of emission clumps for future monitoring of fossil fuel CO2 emissions from space, Earth Syst. Sci. Data, 11, 687–703, https://doi.org/10.5194/essd-11-687-2019, 2019. a
Wang, Y., Broquet, G., Bréon, F.-M.,
Lespinas, F., Buchwitz, M., Reuter, M., Meijer, Y., Loescher, A., Janssens-Maenhout, G., Zheng, B., and Ciais, P.: PMIF v1.0: assessing the potential of satellite observations to constrain CO2 emissions from large cities and point sources over the globe using synthetic data, Geosci. Model Dev., 13, 5813–5831, https://doi.org/10.5194/gmd-13-5813-2020, 2020. a, b, c
Wu, D., Lin, J. C., Oda, T., and Kort,
E. A.: Space-based quantification of per capita CO2 emissions from cities,
Environ. Res. Lett., 15, 035004, https://doi.org/10.1088/1748-9326/ab68eb, 2020. a
Zheng, B., Chevallier, F., Ciais, P., Broquet, G., Wang, Y., Lian, J., and Zhao, Y.: Observing
carbon dioxide emissions over China's cities and industrial areas with the Orbiting Carbon
Observatory-2, Atmos. Chem. Phys., 20, 8501–8510, https://doi.org/10.5194/acp-20-8501-2020, 2020. a
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Short summary
The European CO2M mission is a proposed constellation of CO2 imaging satellites expected to monitor CO2 emissions of large cities. Using synthetic observations, we show that a constellation of two or more satellites should be able to quantify Berlin's annual emissions with 10–20 % accuracy, even when considering atmospheric transport model errors. We therefore expect that CO2M will make an important contribution to the monitoring and verification of CO2 emissions from cities worldwide.
The European CO2M mission is a proposed constellation of CO2 imaging satellites expected to...
