Articles | Volume 17, issue 8
https://doi.org/10.5194/amt-17-2257-2024
© Author(s) 2024. 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-17-2257-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantitative imaging of carbon dioxide plumes using a ground-based shortwave infrared spectral camera
Marvin Knapp
CORRESPONDING AUTHOR
Institute of Environmental Physics (IUP), Heidelberg University, Heidelberg, Germany
Ralph Kleinschek
Institute of Environmental Physics (IUP), Heidelberg University, Heidelberg, Germany
Sanam N. Vardag
Institute of Environmental Physics (IUP), Heidelberg University, Heidelberg, Germany
Heidelberg Center for the Environment (HCE), Heidelberg University, Heidelberg, Germany
Felix Külheim
Institute of Environmental Physics (IUP), Heidelberg University, Heidelberg, Germany
Helge Haveresch
Institute of Environmental Physics (IUP), Heidelberg University, Heidelberg, Germany
Moritz Sindram
Institute of Environmental Physics (IUP), Heidelberg University, Heidelberg, Germany
Tim Siegel
Institute of Environmental Physics (IUP), Heidelberg University, Heidelberg, Germany
Bruno Burger
Fraunhofer Institute for Solar Energy Systems (ISE), Heidenhofstr. 2, 79110 Freiburg, Germany
André Butz
Institute of Environmental Physics (IUP), Heidelberg University, Heidelberg, Germany
Heidelberg Center for the Environment (HCE), Heidelberg University, Heidelberg, Germany
Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany
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Astrid Müller, Hiroshi Tanimoto, Takafumi Sugita, Prabir K. Patra, Shin-ichiro Nakaoka, Toshinobu Machida, Isamu Morino, André Butz, and Kei Shiomi
Atmos. Meas. Tech., 17, 1297–1316, https://doi.org/10.5194/amt-17-1297-2024, https://doi.org/10.5194/amt-17-1297-2024, 2024
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Satellite CH4 observations with high accuracy are needed to understand changes in atmospheric CH4 concentrations. But over oceans, reference data are limited. We combine various ship and aircraft observations with the help of atmospheric chemistry models to derive observation-based column-averaged mixing ratios of CH4 (obs. XCH4). We discuss three different approaches and demonstrate the applicability of the new reference dataset for carbon cycle studies and satellite evaluation.
Tobias D. Schmitt, Jonas Kuhn, Ralph Kleinschek, Benedikt A. Löw, Stefan Schmitt, William Cranton, Martina Schmidt, Sanam N. Vardag, Frank Hase, David W. T. Griffith, and André Butz
Atmos. Meas. Tech., 16, 6097–6110, https://doi.org/10.5194/amt-16-6097-2023, https://doi.org/10.5194/amt-16-6097-2023, 2023
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Our new observatory measures greenhouse gas concentrations of carbon dioxide (CO2) and methane (CH4) along a 1.55 km long light path over the city of Heidelberg, Germany. We compared our measurements with measurements that were taken at a single point at one end of our path. The two mostly agreed but show a significant difference for CO2 with certain wind directions. This is important when using greenhouse gas concentration measurements to observe greenhouse gas emissions of cities.
Benedikt A. Löw, Ralph Kleinschek, Vincent Enders, Stanley P. Sander, Thomas J. Pongetti, Tobias D. Schmitt, Frank Hase, Julian Kostinek, and André Butz
Atmos. Meas. Tech., 16, 5125–5144, https://doi.org/10.5194/amt-16-5125-2023, https://doi.org/10.5194/amt-16-5125-2023, 2023
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We developed a portable spectrometer (EM27/SCA) that remotely measures greenhouse gases in the lower atmosphere above a target region. The measurements can deliver insights into local emission patterns. To evaluate its performance, we set up the EM27/SCA above the Los Angeles Basin side by side with a similar non-portable instrument (CLARS-FTS). The precision is promising and the measurements are consistent with CLARS-FTS. In the future, we need to account for light scattering.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, Andre Butz, Otto P. Hasekamp, Lianghai Wu, and Jochen Landgraf
Atmos. Meas. Tech., 15, 6585–6603, https://doi.org/10.5194/amt-15-6585-2022, https://doi.org/10.5194/amt-15-6585-2022, 2022
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Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
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We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Andreas Luther, Julian Kostinek, Ralph Kleinschek, Sara Defratyka, Mila Stanisavljević, Andreas Forstmaier, Alexandru Dandocsi, Leon Scheidweiler, Darko Dubravica, Norman Wildmann, Frank Hase, Matthias M. Frey, Jia Chen, Florian Dietrich, Jarosław Nȩcki, Justyna Swolkień, Christoph Knote, Sanam N. Vardag, Anke Roiger, and André Butz
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Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
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Qiansi Tu, Frank Hase, Matthias Schneider, Omaira García, Thomas Blumenstock, Tobias Borsdorff, Matthias Frey, Farahnaz Khosrawi, Alba Lorente, Carlos Alberti, Juan J. Bustos, André Butz, Virgilio Carreño, Emilio Cuevas, Roger Curcoll, Christopher J. Diekmann, Darko Dubravica, Benjamin Ertl, Carme Estruch, Sergio Fabián León-Luis, Carlos Marrero, Josep-Anton Morgui, Ramón Ramos, Christian Scharun, Carsten Schneider, Eliezer Sepúlveda, Carlos Toledano, and Carlos Torres
Atmos. Chem. Phys., 22, 295–317, https://doi.org/10.5194/acp-22-295-2022, https://doi.org/10.5194/acp-22-295-2022, 2022
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We use different methane ground- and space-based remote sensing data sets for investigating the emission strength of three waste disposal sites close to Madrid. We present a method that uses wind-assigned anomalies for deriving emission strengths from satellite data and estimate their uncertainty to 9–14 %. The emission strengths estimated from the remote sensing data sets are significantly larger than the values published in the official register.
Julian Kostinek, Anke Roiger, Maximilian Eckl, Alina Fiehn, Andreas Luther, Norman Wildmann, Theresa Klausner, Andreas Fix, Christoph Knote, Andreas Stohl, and André Butz
Atmos. Chem. Phys., 21, 8791–8807, https://doi.org/10.5194/acp-21-8791-2021, https://doi.org/10.5194/acp-21-8791-2021, 2021
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Abundant mining and industrial activities in the Upper Silesian Coal Basin lead to large emissions of the potent greenhouse gas methane. This study quantifies these emissions with continuous, high-precision airborne measurements and dispersion modeling. Our emission estimates are in line with values reported in the European Pollutant Release and Transfer Register (E-PRTR 2017) but significantly lower than values reported in the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2).
Hiroshi Suto, Fumie Kataoka, Nobuhiro Kikuchi, Robert O. Knuteson, Andre Butz, Markus Haun, Henry Buijs, Kei Shiomi, Hiroko Imai, and Akihiko Kuze
Atmos. Meas. Tech., 14, 2013–2039, https://doi.org/10.5194/amt-14-2013-2021, https://doi.org/10.5194/amt-14-2013-2021, 2021
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The Japanese Greenhouse gases Observing SATellite-2 (GOSAT-2), in orbit since October 2018, is the follow-up mission of GOSAT, which has been operating since January 2009. Both satellites are dedicated to the monitoring of global carbon dioxide and methane to further knowledge of the global carbon cycle. This paper has reported on the function and performance of the TANSO-FTS-2 instrument, level-1 data processing, and calibrations for the first year of GOSAT-2 observation.
Marvin Knapp, Ralph Kleinschek, Frank Hase, Anna Agustí-Panareda, Antje Inness, Jérôme Barré, Jochen Landgraf, Tobias Borsdorff, Stefan Kinne, and André Butz
Earth Syst. Sci. Data, 13, 199–211, https://doi.org/10.5194/essd-13-199-2021, https://doi.org/10.5194/essd-13-199-2021, 2021
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We developed a shipborne variant of a remote sensing spectrometer for direct sunlight measurements of column-averaged atmospheric mixing ratios of carbon dioxide, methane, and carbon monoxide. The instrument was deployed on the research vessel Sonne during a longitudinal transect over the Pacific during June 2019. The campaign yielded more than 32 000 observations which compare excellently to atmospheric composition data from a state-of-the-art model (CAMS) and satellite observations (TROPOMI).
Alba Lorente, Tobias Borsdorff, Andre Butz, Otto Hasekamp, Joost aan de Brugh, Andreas Schneider, Lianghai Wu, Frank Hase, Rigel Kivi, Debra Wunch, David F. Pollard, Kei Shiomi, Nicholas M. Deutscher, Voltaire A. Velazco, Coleen M. Roehl, Paul O. Wennberg, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, https://doi.org/10.5194/amt-14-665-2021, 2021
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TROPOMI aboard Sentinel-5P satellite provides methane (CH4) measurements with exceptional temporal and spatial resolution. The study describes a series of improvements developed to retrieve CH4 from TROPOMI. The updated CH4 product features (among others) a more accurate a posteriori correction derived independently of any reference data. The validation of the improved data product shows good agreement with ground-based and satellite measurements, which highlights the quality of the TROPOMI CH4.
Cited articles
Adler, B., Gohm, A., Kalthoff, N., Babić, N., Corsmeier, U., Lehner, M., Rotach, M. W., Haid, M., Markmann, P., Gast, E., Tsaknakis, G., and Georgoussis, G.: CROSSINN: A Field Experiment to Study the Three-Dimensional Flow Structure in the Inn Valley, Austria, B. Am. Meteorol. Soc., 102, E38–E60, https://doi.org/10.1175/BAMS-D-19-0283.1, 2021. a
Anderson, G., Clough, S., Kneizys, F., Chetwyd, J., and Shettle, E.: AFGL Atmospheric Constituent Profiles (0–120 km), Air Force Geophysics Laboratory Tech. Rep, Tech. rep., AFGL-TR-86-0110, 1986. a
Ayasse, A. K., Thorpe, A. K., Roberts, D. A., Funk, C. C., Dennison, P. E., Frankenberg, C., Steffke, A., and Aubrey, A. D.: Evaluating the Effects of Surface Properties on Methane Retrievals Using a Synthetic Airborne Visible/Infrared Imaging Spectrometer next Generation (AVIRIS-NG) Image, Remote Sens. Environ., 215, 386–397, https://doi.org/10.1016/j.rse.2018.06.018, 2018. a
Bevington, P. R., Robinson, D. K., Blair, J. M., Mallinckrodt, A. J., and McKay, S.: Data Reduction and Error Analysis for the Physical Sciences, Comput. Phys., 7, 415, https://doi.org/10.1063/1.4823194, 1993. a
Borsdorff, T., aan de Brugh, J., Schneider, A., Lorente, A., Birk, M., Wagner, G., Kivi, R., Hase, F., Feist, D. G., Sussmann, R., Rettinger, M., Wunch, D., Warneke, T., and Landgraf, J.: Improving the TROPOMI CO data product: update of the spectroscopic database and destriping of single orbits, Atmos. Meas. Tech., 12, 5443–5455, https://doi.org/10.5194/amt-12-5443-2019, 2019. 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
Candès, E. J., Wakin, M. B., and Boyd, S. P.: Enhancing Sparsity by Reweighted L1 Minimization, J. Fourier Anal. Appl., 14, 877–905, https://doi.org/10.1007/s00041-008-9045-x, 2008. a
Carhart, R. and Policastro, A.: A Second-Generation Model for Cooling Tower Plume Rise and Dispersion – I. Single Sources, Atmos. Environ. A-Gen., 25, 1559–1576, https://doi.org/10.1016/0960-1686(91)90015-Y, 1991. a
Christen, A.: Atmospheric Measurement Techniques to Quantify Greenhouse Gas Emissions from Cities, Urban Climate, 10, 241–260, https://doi.org/10.1016/j.uclim.2014.04.006, 2014. a
Christen, A., Coops, N., Crawford, B., Kellett, R., Liss, K., Olchovski, I., Tooke, T., van der Laan, M., and Voogt, J.: Validation of Modeled Carbon-Dioxide Emissions from an Urban Neighborhood with Direct Eddy-Covariance Measurements, Atmos. Environ., 45, 6057–6069, https://doi.org/10.1016/j.atmosenv.2011.07.040, 2011. a
Crawford, B. and Christen, A.: Spatial Source Attribution of Measured Urban Eddy Covariance CO2 Fluxes, Theor. Appl. Climatol., 119, 733–755, https://doi.org/10.1007/s00704-014-1124-0, 2015. a
Cusworth, D. H., Duren, R. M., Thorpe, A. K., Eastwood, M. L., Green, R. O., Dennison, P. E., Frankenberg, C., Heckler, J. W., Asner, G. P., and Miller, C. E.: Quantifying Global Power Plant Carbon Dioxide Emissions With Imaging Spectroscopy, AGU Advances, 2, e2020AV000350, https://doi.org/10.1029/2020AV000350, 2021a. a
Cusworth, D. H., Duren, R. M., Thorpe, A. K., Olson-Duvall, W., Heckler, J., Chapman, J. W., Eastwood, M. L., Helmlinger, M. C., Green, R. O., Asner, G. P., Dennison, P. E., and Miller, C. E.: Intermittency of Large Methane Emitters in the Permian Basin, Environ. Sci. Technol. Lett., 8, 567–573, https://doi.org/10.1021/acs.estlett.1c00173, 2021b. a
Dennison, P. E., Thorpe, A. K., Pardyjak, E. R., Roberts, D. A., Qi, Y., Green, R. O., Bradley, E. S., and Funk, C. C.: High Spatial Resolution Mapping of Elevated Atmospheric Carbon Dioxide Using Airborne Imaging Spectroscopy: Radiative Transfer Modeling and Power Plant Plume Detection, Remote Sens. Environ., 139, 116–129, https://doi.org/10.1016/j.rse.2013.08.001, 2013. a
Dörner, S., Donner, S., Behrens, L., Beirle, S., and Wagner, T.: MAX-DOAS Measurements of Tropospheric Trace Gases during the AQABA Campaign in Late Summer 2017, in: EGU General Assembly Conference Abstracts, p. 4978, Vienna, Austria, 8–13 April 2018, https://meetingorganizer.copernicus.org/EGU2018/EGU2018-6027.pdf (last access: 11 April 2024), 2018. a
Duren, R. M., Thorpe, A. K., Foster, K. T., Rafiq, T., Hopkins, F. M., Yadav, V., Bue, B. D., Thompson, D. R., Conley, S., Colombi, N. K., Frankenberg, C., McCubbin, I. B., Eastwood, M. L., Falk, M., Herner, J. D., Croes, B. E., Green, R. O., and Miller, C. E.: California's Methane Super-Emitters, Nature, 575, 180–184, https://doi.org/10.1038/s41586-019-1720-3, 2019. a
Foote, M. D., Dennison, P. E., Thorpe, A. K., Thompson, D. R., Jongaramrungruang, S., Frankenberg, C., and Joshi, S. C.: Fast and Accurate Retrieval of Methane Concentration From Imaging Spectrometer Data Using Sparsity Prior, IEEE T. Geosci. Remote, 58, 6480–6492, https://doi.org/10.1109/TGRS.2020.2976888, 2020. a, b, c, d, e, f
Foote, M. D., Dennison, P. E., Sullivan, P. R., O'Neill, K. B., Thorpe, A. K., Thompson, D. R., Cusworth, D. H., Duren, R., and Joshi, S. C.: Impact of Scene-Specific Enhancement Spectra on Matched Filter Greenhouse Gas Retrievals from Imaging Spectroscopy, Remote Sens. Environ., 264, 112574, https://doi.org/10.1016/j.rse.2021.112574, 2021. a, b, c
Frankenberg, C., Thorpe, A. K., Thompson, D. R., Hulley, G., Kort, E. A., Vance, N., Borchardt, J., Krings, T., Gerilowski, K., Sweeney, C., Conley, S., Bue, B. D., Aubrey, A. D., Hook, S., and Green, R. O.: Airborne Methane Remote Measurements Reveal Heavy-Tail Flux Distribution in Four Corners Region, P. Natl. Acad. Sci. USA, 113, 9734–9739, https://doi.org/10.1073/pnas.1605617113, 2016. a
Fujinawa, T., Kuze, A., Suto, H., Shiomi, K., Kanaya, Y., Kawashima, T., Kataoka, F., Mori, S., Eskes, H., and Tanimoto, H.: First Concurrent Observations of NO2 and CO2 From Power Plant Plumes by Airborne Remote Sensing, Geophys. Res. Lett., 48, e2021GL092685, https://doi.org/10.1029/2021GL092685, 2021. a
Gålfalk, M., Olofsson, G., Crill, P., and Bastviken, D.: Making Methane Visible, Nat. Clim. Change, 6, 426–430, https://doi.org/10.1038/nclimate2877, 2016. a
Gordon, I., Rothman, L., Hill, C., Kochanov, R., Tan, Y., Bernath, P., Birk, M., Boudon, V., Campargue, A., Chance, K., Drouin, B., Flaud, J.-M., Gamache, R., Hodges, J., Jacquemart, D., Perevalov, V., Perrin, A., Shine, K., Smith, M.-A., Tennyson, J., Toon, G., Tran, H., Tyuterev, V., Barbe, A., Császár, A., Devi, V., Furtenbacher, T., Harrison, J., Hartmann, J.-M., Jolly, A., Johnson, T., Karman, T., Kleiner, I., Kyuberis, A., Loos, J., Lyulin, O., Massie, S., Mikhailenko, S., Moazzen-Ahmadi, N., Müller, H., Naumenko, O., Nikitin, A., Polyansky, O., Rey, M., Rotger, M., Sharpe, S., Sung, K., Starikova, E., Tashkun, S., Auwera, J. V., Wagner, G., Wilzewski, J., Wcisło, P., Yu, S., and Zak, E.: The HITRAN2016 Molecular Spectroscopic Database, J. Quant. Spectrosc. Ra., 203, 3–69, https://doi.org/10.1016/j.jqsrt.2017.06.038, 2017. a
Grosskraftwerk, M.: Geschäftsbericht 2015, Annual report, Grosskraftwerk Mannheim, https://www.gkm.de/unternehmen/#n5 (last access: 3 November 2021), 2015. a
Guanter, L., Irakulis-Loitxate, I., Gorroño, J., Sánchez-García, E., Cusworth, D. H., Varon, D. J., Cogliati, S., and Colombo, R.: Mapping Methane Point Emissions with the PRISMA Spaceborne Imaging Spectrometer, Remote Sens. Environ., 265, 112671, https://doi.org/10.1016/j.rse.2021.112671, 2021. a, b, c, d
Hase, F., Frey, M., Blumenstock, T., Groß, J., Kiel, M., Kohlhepp, R., Mengistu Tsidu, G., Schäfer, K., Sha, M. K., and Orphal, J.: Application of portable FTIR spectrometers for detecting greenhouse gas emissions of the major city Berlin, Atmos. Meas. Tech., 8, 3059–3068, https://doi.org/10.5194/amt-8-3059-2015, 2015. a
Henyey, L. and Greenstein, J.: Diffuse Radiation in the Galaxy, Astrophys. J., 93, 70–83, 1941. a
Holmgren, F., Hansen, C. W., and Mikofski, M. A.: Pvlib Python: A Python Package for Modeling Solar Energy Systems, Journal of Open Source Software, 3, 884, https://doi.org/10.21105/joss.00884, 2018. a
Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A.-M., Dominguez, J. J., Engelen, R., Eskes, H., Flemming, J., Huijnen, V., Jones, L., Kipling, Z., Massart, S., Parrington, M., Peuch, V.-H., Razinger, M., Remy, S., Schulz, M., and Suttie, M.: The CAMS reanalysis of atmospheric composition, Atmos. Chem. Phys., 19, 3515–3556, https://doi.org/10.5194/acp-19-3515-2019, 2019. a
Jacob, D. J., Varon, D. J., Cusworth, D. H., Dennison, P. E., Frankenberg, C., Gautam, R., Guanter, L., Kelley, J., McKeever, J., Ott, L. E., Poulter, B., Qu, Z., Thorpe, A. K., Worden, J. R., and Duren, R. M.: Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane, Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, 2022. a
Janicke, U. and Janicke, L.: A Three-Dimensional Plume Rise Model for Dry and Wet Plumes, Atmos. Environ., 35, 877–890, https://doi.org/10.1016/S1352-2310(00)00372-1, 2001. a, b, c, d
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., E1439–E1451, https://doi.org/10.1175/BAMS-D-19-0017.1, 2020. a
Jongaramrungruang, S., Frankenberg, C., Matheou, G., Thorpe, A. K., Thompson, D. R., Kuai, L., and Duren, R. M.: Towards accurate methane point-source quantification from high-resolution 2-D plume imagery, Atmos. Meas. Tech., 12, 6667–6681, https://doi.org/10.5194/amt-12-6667-2019, 2019. a
Jongaramrungruang, S., Thorpe, A. K., Matheou, G., and Frankenberg, C.: MethaNet – An AI-driven Approach to Quantifying Methane Point-Source Emission from High-Resolution 2-D Plume Imagery, Remote Sens. Environ., 269, 112809, https://doi.org/10.1016/j.rse.2021.112809, 2022. a
Jungmann, M., Vardag, S. N., Kutzner, F., Keppler, F., Schmidt, M., Aeschbach, N., Gerhard, U., Zipf, A., Lautenbach, S., Siegmund, A., Goeschl, T., and Butz, A.: Zooming-in for Climate Action – Hyperlocal Greenhouse Gas Data for Mitigation Action?, Climate Action, 1, 8, https://doi.org/10.1007/s44168-022-00007-4, 2022. a
Kasten, F. and Young, A. T.: Revised Optical Air Mass Tables and Approximation Formula, Appl. Optics, 28, 4735, https://doi.org/10.1364/AO.28.004735, 1989. a
Kiel, M., Eldering, A., Roten, D. D., Lin, J. C., Feng, S., Lei, R., Lauvaux, T., Oda, T., Roehl, C. M., Blavier, J.-F., and Iraci, L. T.: Urban-Focused Satellite CO2 Observations from the Orbiting Carbon Observatory-3: A First Look at the Los Angeles Megacity, Remote Sens. Environ., 258, 112314, https://doi.org/10.1016/j.rse.2021.112314, 2021. a
Knapp, M., Scheidweiler, L., Külheim, F., Kleinschek, R., Necki, J., Jagoda, P., and Butz, A.: Spectrometric Imaging of Sub-Hourly Methane Emission Dynamics from Coal Mine Ventilation, Environ. Res. Lett., 18, 044030, https://doi.org/10.1088/1748-9326/acc346, 2023. a, b
Köhler, P., Guanter, L., and Joiner, J.: A linear method for the retrieval of sun-induced chlorophyll fluorescence from GOME-2 and SCIAMACHY data, Atmos. Meas. Tech., 8, 2589–2608, https://doi.org/10.5194/amt-8-2589-2015, 2015. a
Kort, E. A., Frankenberg, C., Miller, C. E., and Oda, T.: Space-Based Observations of Megacity Carbon Dioxide: SPACE-BASED OBSERVATIONS OF MEGACITY CO2, Geophys. Res. Lett., 39, L17806, https://doi.org/10.1029/2012GL052738, 2012. a
Krings, T., Gerilowski, K., Buchwitz, M., Reuter, M., Tretner, A., Erzinger, J., Heinze, D., Pflüger, U., Burrows, J. P., and Bovensmann, H.: MAMAP – a new spectrometer system for column-averaged methane and carbon dioxide observations from aircraft: retrieval algorithm and first inversions for point source emission rates, Atmos. Meas. Tech., 4, 1735–1758, https://doi.org/10.5194/amt-4-1735-2011, 2011. a
Lenhard, K., Baumgartner, A., and Schwarzmaier, T.: Independent Laboratory Characterization of NEO HySpex Imaging Spectrometers VNIR-1600 and SWIR-320m-e, IEEE T. Geosci. Remote, 53, 1828–1841, https://doi.org/10.1109/TGRS.2014.2349737, 2015. a
Liu, M., van der A, R., van Weele, M., Eskes, H., Lu, X., Veefkind, P., de Laat, J., Kong, H., Wang, J., Sun, J., Ding, J., Zhao, Y., and Weng, H.: A New Divergence Method to Quantify Methane Emissions Using Observations of Sentinel-5P TROPOMI, Geophys. Res. Lett., 48, e2021GL094151, https://doi.org/10.1029/2021GL094151, 2021. a
Luther, A., Kostinek, J., Kleinschek, R., Defratyka, S., Stanisavljević, M., Forstmaier, A., Dandocsi, A., Scheidweiler, L., Dubravica, D., Wildmann, N., Hase, F., Frey, M. M., Chen, J., Dietrich, F., Nȩcki, J., Swolkień, J., Knote, C., Vardag, S. N., Roiger, A., and Butz, A.: Observational constraints on methane emissions from Polish coal mines using a ground-based remote sensing network, Atmos. Chem. Phys., 22, 5859–5876, https://doi.org/10.5194/acp-22-5859-2022, 2022. a
Manolakis, D., Truslow, E., Pieper, M., Cooley, T., and Brueggeman, M.: Detection Algorithms in Hyperspectral Imaging Systems: An Overview of Practical Algorithms, IEEE Signal Proc. Mag., 31, 24–33, https://doi.org/10.1109/MSP.2013.2278915, 2014. a
Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Chaud, N., Chen, Y., Goldfarb, L., Gomis, M., Huang, M., Leitzell, K., Lonnoy, E., Metthews, J., Maycook, T., Waterfield, T., Yelekci, O., Yu, R., and Zhou, B.: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Tech. rep., Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896, 2021. a
Matheou, G. and Bowman, K. W.: A Recycling Method for the Large-Eddy Simulation of Plumes in the Atmospheric Boundary Layer, Environ. Fluid Mech., 16, 69–85, https://doi.org/10.1007/s10652-015-9413-4, 2016. 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, b, c
Pei, Z., Han, G., Mao, H., Chen, C., Shi, T., Yang, K., Ma, X., and Gong, W.: Improving Quantification of Methane Point Source Emissions from Imaging Spectroscopy, Remote Sens. Environ., 295, 113652, https://doi.org/10.1016/j.rse.2023.113652, 2023. a
Peters, G.: Reliable Data – Continuous Wave Lidars Can Provide More Accurate Wind Measurements with High Resolution at Short Distances, Meteorological Technology International, https://www.alliance-technologies.net/app/uploads/2020/03/20180620_Meteo-Article_WindRanger.pdf (last access: 5 May 2022) 106–108, 2018. a
Rayner, P. J., Utembe, S. R., and Crowell, S.: Constraining regional greenhouse gas emissions using geostationary concentration measurements: a theoretical study, Atmos. Meas. Tech., 7, 3285–3293, https://doi.org/10.5194/amt-7-3285-2014, 2014. a
Sandau, F., Timme, S., Baumgarten, C., Beckers, R., Bretschneider, D. W., Briem, S., Frauenstein, J., Gibis, C., Gniffke, P., Grimm, S., Herbstritt, C., and Juhrich, K.: Daten und Fakten zu Braun- und Steinkohlen: Stand und Perspektiven 2021, https://www.umweltbundesamt.de/sites/default/files/medien/1410/publikationen/2023-01-05_texte_28-2021_daten_fakten_braun-_und_steinkohle.pdf (last access: 1 August 2022), 2021. a
Schaum, A.: A Uniformly Most Powerful Detector of Gas Plumes against a Cluttered Background, Remote Sens. Environ., 260, 112443, https://doi.org/10.1016/j.rse.2021.112443, 2021. a
Schwandner, F. M., Gunson, M. R., Miller, C. E., Carn, S. A., Eldering, A., Krings, T., Verhulst, K. R., Schimel, D. S., Nguyen, H. M., Crisp, D., O'Dell, C. W., Osterman, G. B., Iraci, L. T., and Podolske, J. R.: Spaceborne Detection of Localized Carbon Dioxide Sources, Science, 358, eaam5782, https://doi.org/10.1126/science.aam5782, 2017. a, b, c
Slater, J. A. and Malys, S.: WGS 84 – Past, Present and Future, in: Advances in Positioning and Reference Frames, edited by: Schwarz, K.-P. and Brunner, F. K., Springer Berlin Heidelberg, Berlin, Heidelberg, ISBN 978-3-662-03714-0, vol. 118, 1–7, https://doi.org/10.1007/978-3-662-03714-0_1, 1998. a
Strandgren, J., Krutz, D., Wilzewski, J., Paproth, C., Sebastian, I., Gurney, K. R., Liang, J., Roiger, A., and Butz, A.: Towards spaceborne monitoring of localized CO2 emissions: an instrument concept and first performance assessment, Atmos. Meas. Tech., 13, 2887–2904, https://doi.org/10.5194/amt-13-2887-2020, 2020. a
Thompson, D. R., Leifer, I., Bovensmann, H., Eastwood, M., Fladeland, M., Frankenberg, C., Gerilowski, K., Green, R. O., Kratwurst, S., Krings, T., Luna, B., and Thorpe, A. K.: Real-time remote detection and measurement for airborne imaging spectroscopy: a case study with methane, Atmos. Meas. Tech., 8, 4383–4397, https://doi.org/10.5194/amt-8-4383-2015, 2015. a
Thorpe, A. K., Roberts, D. A., Bradley, E. S., Funk, C. C., Dennison, P. E., and Leifer, I.: High Resolution Mapping of Methane Emissions from Marine and Terrestrial Sources Using a Cluster-Tuned Matched Filter Technique and Imaging Spectrometry, Remote Sens. Environ., 134, 305–318, https://doi.org/10.1016/j.rse.2013.03.018, 2013. a
Thorpe, A. K., Frankenberg, C., Thompson, D. R., Duren, R. M., Aubrey, A. D., Bue, B. D., Green, R. O., Gerilowski, K., Krings, T., Borchardt, J., Kort, E. A., Sweeney, C., Conley, S., Roberts, D. A., and Dennison, P. E.: Airborne DOAS retrievals of methane, carbon dioxide, and water vapor concentrations at high spatial resolution: application to AVIRIS-NG, Atmos. Meas. Tech., 10, 3833–3850, https://doi.org/10.5194/amt-10-3833-2017, 2017. a, b
Varon, D. J., Jacob, D. J., McKeever, J., Jervis, D., Durak, B. O. A., Xia, Y., and Huang, Y.: Quantifying methane point sources from fine-scale satellite observations of atmospheric methane plumes, Atmos. Meas. Tech., 11, 5673–5686, https://doi.org/10.5194/amt-11-5673-2018, 2018. a, b, c
Varon, D. J., Jacob, D. J., Jervis, D., and McKeever, J.: Quantifying Time-Averaged Methane Emissions from Individual Coal Mine Vents with GHGSat-D Satellite Observations, Environ. Sci. Technol., 54, 10246–10253, https://doi.org/10.1021/acs.est.0c01213, 2020. a
Zhang, Y., Gautam, R., Pandey, S., Omara, M., Maasakkers, J. D., Sadavarte, P., Lyon, D., Nesser, H., Sulprizio, M. P., Varon, D. J., Zhang, R., Houweling, S., Zavala-Araiza, D., Alvarez, R. A., Lorente, A., Hamburg, S. P., Aben, I., and Jacob, D. J.: Quantifying Methane Emissions from the Largest Oil-Producing Basin in the United States from Space, Sci. Adv., 6, eaaz5120, https://doi.org/10.1126/sciadv.aaz5120, 2020. a
Executive editor
Following the handling editor recommendation, the manuscript presents innovative analysis of a ground-based imaging experiment using a shortwave infrared spectral camera to quantify carbon dioxide (CO2) emissions from a coal-fired power plant. The innovation of the manuscript is to use low spectral resolution (7nm) imaging spectroscopy to measure CO2 plume structure and estimate emission amounts from chimneys by the ground-based observation. The methodology has potential important applications for fine-scale estimates of CO2 and other GHG emissions
Following the handling editor recommendation, the manuscript presents innovative analysis of a...
Short summary
Imaging carbon dioxide (CO2) plumes of anthropogenic sources from planes and satellites has proven valuable for detecting emitters and monitoring climate mitigation efforts. We present the first images of CO2 plumes taken with a ground-based spectral camera, observing a coal-fired power plant as a validation target. We develop a technique to find the source emission strength with an hourly resolution, which reasonably agrees with the expected emissions under favorable conditions.
Imaging carbon dioxide (CO2) plumes of anthropogenic sources from planes and satellites has...