Articles | Volume 17, issue 3
https://doi.org/10.5194/amt-17-1145-2024
https://doi.org/10.5194/amt-17-1145-2024
Research article
 | 
16 Feb 2024
Research article |  | 16 Feb 2024

A method for estimating localized CO2 emissions from co-located satellite XCO2 and NO2 images

Blanca Fuentes Andrade, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Andreas Richter, Hartmut Boesch, and John P. Burrows

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Cited articles

Bell, E., O'Dell, C. W., Taylor, T. E., Merrelli, A., Nelson, R. R., Kiel, M., Eldering, A., Rosenberg, R., and Fisher, B.: Exploring bias in the OCO-3 snapshot area mapping mode via geometry, surface, and aerosol effects, Atmos. Meas. Tech., 16, 109–133, https://doi.org/10.5194/amt-16-109-2023, 2023. a
Bergamaschi, P., Danila, A. M., Weiss, R., Ciais, P., Thompson, R. L., Brunner, D., Levin, I., Meijer, Y., Chevallier, F., Janssens-Maenhout, G., Bovensmann, H., Crisp, D., Basu, S., Dlugokencky, E., Engelen, R., Gerbig, C., Günther, D., Hammer, S., Henne, S., Houweling, S., Karstens, U., Kort, E., Maione, M., Manning, A., Miller, J., Montzka, S., Pandey, S., Peters, W., Peylin, P., Pinty, B., Ramonet, M., Reimann, S., Röckmann, T., Schmidt, M., Strogies, M., Sussams, J., Tarasova, O., Van, A. J., Vermeulen, A., and Vogel, F.: Atmospheric monitoring and inverse modelling for verification of greenhouse gas inventories, Publications Office of the European Union, https://doi.org/10.2760/759928, 2018. a
Bézy, J.-L., Sierk, B., Löscher, A., Meijer, Y., Nett, H., and Fernandez, V.: The European Copernicus Anthropogenic CO2 Monitoring Mission, in: IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 28 July–2 August 2019, IEEE, 8400–8403, ISSN 2153-7003, https://doi.org/10.1109/IGARSS.2019.8899116, 2019. a
Bovensmann, H., Burrows, J. P., Buchwitz, M., Frerick, J., Noël, S., Rozanov, V. V., Chance, K. V., and Goede, A. P. H.: SCIAMACHY: Mission Objectives and Measurement Modes, J. Atmos. Sci., 56, 127–150, https://doi.org/10.1175/1520-0469(1999)056<0127:SMOAMM>2.0.CO;2, 1999. 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, b, c, d
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Short summary
We developed a method to estimate CO2 emissions from localized sources, such as power plants, using satellite data and applied it to estimate CO2 emissions from the Bełchatów Power Station (Poland). As the detection of CO2 emission plumes from satellite data is difficult, we used observations of co-emitted NO2 to constrain the emission plume region. Our results agree with CO2 emission estimations based on the power-plant-generated power and emission factors.