Articles | Volume 13, issue 12
https://doi.org/10.5194/amt-13-6755-2020
© 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-13-6755-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantifying the impact of aerosol scattering on the retrieval of methane from airborne remote sensing measurements
Yunxia Huang
School of Science, Nantong University, Nantong, 226007, China
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Zhao-Cheng Zeng
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA
Joint Institute for Regional Earth System Science and Engineering,
University of California, Los Angeles, CA 90095, USA
Pushkar Kopparla
Graduate School of Frontier Sciences, The University of Tokyo,
Kashiwa, Chiba 277-0882, Japan
Yuk L. Yung
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Related authors
No articles found.
Fan Sun, Yu Cui, Jiayin Su, Yifan Zhang, Xuejing Shi, Junqing Zhang, Huili Liu, Qitao Xiao, Xiao Lu, Zhao-Cheng Zeng, Timothy J. Griffis, and Cheng Hu
EGUsphere, https://doi.org/10.5194/egusphere-2025-3090, https://doi.org/10.5194/egusphere-2025-3090, 2025
Short summary
Short summary
This study used satellite data and models to track ammonia concentration and dry deposition across China from 2013 to 2023. Ammonia levels rose sharply, especially in urban and farming regions, with the North China Plain showing the highest values. Human activity was the main driver of change. These findings highlight growing environmental risks and provide key insights for managing air quality and nitrogen pollution in one of the world’s major emission hotspots.
Jan-Lukas Tirpitz, Santo Fedele Colosimo, Nathaniel Brockway, Robert Spurr, Matt Christi, Samuel Hall, Kirk Ullmann, Johnathan Hair, Taylor Shingler, Rodney Weber, Jack Dibb, Richard Moore, Elizabeth Wiggins, Vijay Natraj, Nicolas Theys, and Jochen Stutz
Atmos. Chem. Phys., 25, 1989–2015, https://doi.org/10.5194/acp-25-1989-2025, https://doi.org/10.5194/acp-25-1989-2025, 2025
Short summary
Short summary
We combine plume composition data from the 2019 NASA FIREX-AQ campaign with state-of-the-art radiative transfer modeling techniques to calculate distributions of actinic flux and photolysis frequencies in a wildfire plume. Excellent agreement of the model and observations demonstrates the applicability of this approach to constrain photochemistry in such plumes. We identify limiting factors for the modeling accuracy and discuss spatial and spectral features of the distributions.
Edward Malina, Kevin W. Bowman, Valentin Kantchev, Le Kuai, Thomas P. Kurosu, Kazuyuki Miyazaki, Vijay Natraj, Gregory B. Osterman, Fabiano Oyafuso, and Matthew D. Thill
Atmos. Meas. Tech., 17, 5341–5371, https://doi.org/10.5194/amt-17-5341-2024, https://doi.org/10.5194/amt-17-5341-2024, 2024
Short summary
Short summary
Characterizing the distribution of ozone in the atmosphere is a challenging problem, with current Earth observation satellites using either thermal infrared (TIR) or ultraviolet (UV) instruments, sensitive to different portions of the atmosphere, making it difficult to gain a full picture. In this work, we combine measurements from the TIR and UV instruments Suomi NPP CrIS and Sentinel-5P/TROPOMI to improve sensitivity through the whole atmosphere and improve knowledge of ozone distribution.
Zhonghua He, Ling Gao, Miao Liang, and Zhao-Cheng Zeng
Atmos. Meas. Tech., 17, 2937–2956, https://doi.org/10.5194/amt-17-2937-2024, https://doi.org/10.5194/amt-17-2937-2024, 2024
Short summary
Short summary
Using Gaofen-5B satellite data, this study detected 93 methane plume events from 32 coal mines in Shanxi, China, with emission rates spanning from 761.78 ± 185.00 to 12729.12 ± 4658.13 kg h-1, showing significant variability among sources. This study highlights Gaofen-5B’s capacity for monitoring large methane point sources, offering valuable support in reducing greenhouse gas emissions.
Santo Fedele Colosimo, Nathaniel Brockway, Vijay Natraj, Robert Spurr, Klaus Pfeilsticker, Lisa Scalone, Max Spolaor, Sarah Woods, and Jochen Stutz
Atmos. Meas. Tech., 17, 2367–2385, https://doi.org/10.5194/amt-17-2367-2024, https://doi.org/10.5194/amt-17-2367-2024, 2024
Short summary
Short summary
Cirrus clouds are poorly understood components of the climate system, in part due to the challenge of observing thin, sub-visible ice clouds. We address this issue with a new observational approach that uses the remote sensing of near-infrared ice water absorption features from a high-altitude aircraft. We describe the underlying principle of this approach and present a new procedure to retrieve ice concentration in cirrus clouds. Our retrievals compare well with in situ observations.
Zhao-Cheng Zeng, Lu Lee, Chengli Qi, Lieven Clarisse, and Martin Van Damme
Atmos. Meas. Tech., 16, 3693–3713, https://doi.org/10.5194/amt-16-3693-2023, https://doi.org/10.5194/amt-16-3693-2023, 2023
Short summary
Short summary
This study presents an NH3 retrieval algorithm based on the optimal estimation method for the Geostationary Interferometric Infrared Sounder (GIIRS) on board China’s FengYun-4B satellite (FY-4B/GIIRS). Retrieval results demonstrate the capability of FY-4B/GIIRS in capturing the diurnal NH3 changes in East Asia. This operational geostationary observation by FY-4B/GIIRS represents an important advancement over the twice-per-day observations provided by current low-Earth-orbit (LEO) instruments.
Yuan Wang, Xiaojian Zheng, Xiquan Dong, Baike Xi, and Yuk L. Yung
Atmos. Chem. Phys., 23, 8591–8605, https://doi.org/10.5194/acp-23-8591-2023, https://doi.org/10.5194/acp-23-8591-2023, 2023
Short summary
Short summary
Marine boundary layer clouds remain poorly predicted in global climate models due to multiple entangled uncertainty sources. This study uses the in situ observations from a recent field campaign to constrain and evaluate cloud physics in a simplified version of a climate model. Progress and remaining issues in the cloud physics parameterizations are identified. We systematically evaluate the impacts of large-scale forcing, microphysical scheme, and aerosol concentrations on the cloud property.
Zhao-Cheng Zeng, Lu Lee, and Chengli Qi
Atmos. Meas. Tech., 16, 3059–3083, https://doi.org/10.5194/amt-16-3059-2023, https://doi.org/10.5194/amt-16-3059-2023, 2023
Short summary
Short summary
Observations from geostationary orbit provide contiguous coverage with a high temporal resolution, representing an important advancement over current low-Earth-orbit instruments. Using measurements from GIIRS on board China's FengYun satellite, the world’s first geostationary hyperspectral infrared sounder, we showed the first results of diurnal CO in eastern Asia from a geostationary orbit, which will have great potential in improving local and global air quality and climate research.
Vijay Natraj, Ming Luo, Jean-Francois Blavier, Vivienne H. Payne, Derek J. Posselt, Stanley P. Sander, Zhao-Cheng Zeng, Jessica L. Neu, Denis Tremblay, Longtao Wu, Jacola A. Roman, Yen-Hung Wu, and Leonard I. Dorsky
Atmos. Meas. Tech., 15, 1251–1267, https://doi.org/10.5194/amt-15-1251-2022, https://doi.org/10.5194/amt-15-1251-2022, 2022
Short summary
Short summary
High-fidelity monitoring and forecast of air quality and the hydrological cycle require understanding the vertical distribution of temperature, humidity, and trace gases at high spatiotemporal resolution. We describe a new instrument concept, called the JPL GEO-IR Sounder, that would provide this information for the first time from a single instrument platform. Simulations demonstrate the benefits of combining measurements from multiple wavelengths for this purpose from geostationary orbit.
Siraput Jongaramrungruang, Georgios Matheou, Andrew K. Thorpe, Zhao-Cheng Zeng, and Christian Frankenberg
Atmos. Meas. Tech., 14, 7999–8017, https://doi.org/10.5194/amt-14-7999-2021, https://doi.org/10.5194/amt-14-7999-2021, 2021
Short summary
Short summary
This study shows how precision error and bias in column methane retrieval change with different instrument specifications and the impact of spectrally complex surface albedos on retrievals. We show how surface interferences can be mitigated with an optimal spectral resolution and a higher polynomial degree in a retrieval process. The findings can inform future satellite instrument designs to have robust observations capable of separating real CH4 plume enhancements from surface interferences.
King-Fai Li, Ryan Khoury, Thomas J. Pongetti, Stanley P. Sander, Franklin P. Mills, and Yuk L. Yung
Atmos. Meas. Tech., 14, 7495–7510, https://doi.org/10.5194/amt-14-7495-2021, https://doi.org/10.5194/amt-14-7495-2021, 2021
Short summary
Short summary
Nitrogen dioxide (NO2) plays a dominant role in the stratospheric ozone-destroying catalytic cycle. We have retrieved the diurnal cycle of NO2 over Table Mountain in Southern California, USA, during a week in October 2018. Under clean conditions, we are able to predict the diurnal cycle using standard photochemistry. On a day with significant pollution, we see the effect of NO2 sources in the nearby Los Angeles Basin.
Zhao-Cheng Zeng, Vijay Natraj, Feng Xu, Sihe Chen, Fang-Ying Gong, Thomas J. Pongetti, Keeyoon Sung, Geoffrey Toon, Stanley P. Sander, and Yuk L. Yung
Atmos. Meas. Tech., 14, 6483–6507, https://doi.org/10.5194/amt-14-6483-2021, https://doi.org/10.5194/amt-14-6483-2021, 2021
Short summary
Short summary
Large carbon source regions such as megacities are also typically associated with heavy aerosol loading, which introduces uncertainties in the retrieval of greenhouse gases from reflected and scattered sunlight measurements. In this study, we developed a full physics algorithm to retrieve greenhouse gases in the presence of aerosols and demonstrated its performance by retrieving CO2 and CH4 columns from remote sensing measurements in the Los Angeles megacity.
Yuan Wang, Xiaojian Zheng, Xiquan Dong, Baike Xi, Peng Wu, Timothy Logan, and Yuk L. Yung
Atmos. Chem. Phys., 20, 14741–14755, https://doi.org/10.5194/acp-20-14741-2020, https://doi.org/10.5194/acp-20-14741-2020, 2020
Short summary
Short summary
A recent aircraft field campaign near the Azores in the summer of 2017 provides ample observations of aerosols and clouds with detailed vertical information. This study utilizes those observational data in combination with the aerosol-aware large-eddy simulations and aerosol reanalysis data to examine the significance of the long-range-transported aerosol effect on marine-boundary-layer clouds. It is the first time that the ACE-ENA aircraft campaign data are used for this topic.
Brigitte Rooney, Yuan Wang, Jonathan H. Jiang, Bin Zhao, Zhao-Cheng Zeng, and John H. Seinfeld
Atmos. Chem. Phys., 20, 14597–14616, https://doi.org/10.5194/acp-20-14597-2020, https://doi.org/10.5194/acp-20-14597-2020, 2020
Short summary
Short summary
Wildfires have become increasingly prevalent. Intense smoke consisting of particulate matter (PM) leads to an increased risk of morbidity and mortality. The record-breaking Camp Fire ravaged Northern California for two weeks in 2018. Here, we employ a comprehensive chemical transport model along with ground-based and satellite observations to characterize the PM concentrations across Northern California and to investigate the pollution sensitivity predictions to key parameters of the model.
Cited articles
Alvarez, R. A., Zavala-Araiza, D., Lyon, D. R., Allen, D. T., Barkley, Z.
R., Brandt, A. R., Davis, K. J., Herndon, S. C., Jacob, D. J., Karion, A.,
Kort, E. A., Lamb, B. K., Lauvaux, T., Maasakkers, J. D., Marchese, A. J.,
Omara, M., Pacala, S. W., Peischl, J., Robinson, A. L., Shepson, P. B.,
Sweeney, C., Townsend-Small, A., Wofsy, S. C., and Hamburg, S. P.:
Assessment of methane emissions from the U.S. oil and gas supply chain,
Science, 361, 186–188, https://doi.org/10.1126/science.aar7204, 2018.
Archer, D.: Methane hydrate stability and anthropogenic climate change, Biogeosciences, 4, 521–544, https://doi.org/10.5194/bg-4-521-2007, 2007.
Bradley, E. S., Leifer, I., Roberts, D. A., Dennison, P. E., and Washburn,
L.: Detection of marine methane emissions with AVIRIS band ratios, Geophys.
Res. Lett., 38, L10702, https://doi.org/10.1029/2011GL046729, 2011.
Bubier, J. L. and Moore, T. R.: An ecological perspective on methane
emissions from northern wetlands, Trends Ecol. Evol., 9, 460–464, https://doi.org/10.1016/0169-5347(94)90309-3, 1994.
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.
Butz, A., Galli, A., Hasekamp, O., Landgraf, J., Tol, P., and Aben, I.:
TROPOMI aboard Sentinel-5 Precursor: Prospective performance of CH4
retrievals for aerosol and cirrus loaded atmospheres, Remote Sens. Environ., 120, 267–276, https://doi.org/10.1016/j.rse.2011.05.030, 2012.
Butz, A., Orphal, J., Checa-Garcia, R., Friedl-Vallon, F., von Clarmann, T., Bovensmann, H., Hasekamp, O., Landgraf, J., Knigge, T., Weise, D., Sqalli-Houssini, O., and Kemper, D.: Geostationary Emission Explorer for Europe (G3E): mission concept and initial performance assessment, Atmos. Meas. Tech., 8, 4719–4734, https://doi.org/10.5194/amt-8-4719-2015, 2015.
Clerbaux, C., Hadji-Lazaro, J., Turquety, S., Mégie, G., and Coheur, P.-F.: Trace gas measurements from infrared satellite for chemistry and climate applications, Atmos. Chem. Phys., 3, 1495–1508, https://doi.org/10.5194/acp-3-1495-2003, 2003.
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.
Etiope, G., Feyzullayev, A., and Baciu, C. L.: Terrestrial methane seeps and mud volcanoes: A global perspective of gas origin, Mar. Petrol. Geol., 26, 333–344, https://doi.org/10.1016/j.marpetgeo.2008.03.001, 2009.
Fishman, J. L., Iraci, L. T., Al-Saadi, J., Chance, K., Chavez, F., Chin,
M., Coble, P., Davis, C., DiGiacomo, P. M., Edwards, D., Eldering, A., Goes, J., Herman, J., Hu, C., Jacob, D. J., Jordan, C., Kawa, S. R., Key, R., Liu, X., Lohrenz, S., Mannino, A., Natraj, V., Neil, D., Neu, J., Newchurch, M., Pickering, K., Salisbury, J., Sosik, H., Subramaniam, A., Tzortziou, M., Wang, J., and Wang, M.: The United States' next generation of atmospheric composition and coastal ecosystem measurements: NASA's Geostationary Coastal and Air Pollution Events (GEO-CAPE) Mission, B. Am. Meteorol. Soc., 93, 1547–1566, https://doi.org/10.1175/BAMS-D-11-00201.1, 2012.
Frankenberg, C., Platt, U., and Wagner, T.: Iterative maximum a posteriori (IMAP)-DOAS for retrieval of strongly absorbing trace gases: Model studies for CH4 and CO2 retrieval from near infrared spectra of SCIAMACHY onboard ENVISAT, Atmos. Chem. Phys., 5, 9–22, https://doi.org/10.5194/acp-5-9-2005, 2005.
Frankenberg, C., Meirink, J. F., Bergamaschi, P., Goede, A., P. H., Heimann, M., Körner, S., Platt, U., van Weele, M., and Wagner, T.: Satellite chartography of atmospheric methane from SCIAMACHY on board ENVISAT: Analysis of the years 2003 and 2004, J. Geophys. Res., 111, D07303, https://doi.org/10.1029/2005JD006235, 2006.
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.
Gambacorta, A., Barnet, C. D., Smith, N., Pierce, R. B., Smith, J. W.,
Spackman, J. R., and Goldberg, M.: The NPP and J1 NOAA Unique Combined
Atmospheric Processing System (NUCAPS) for atmospheric thermal sounding:
Recent algorithm enhancements tailored to near real time users applications, 2016 Fall Meeting, AGU, San Francisco, CA, 12–16 December 2016, Abstract IN33D-07, 2016.
Gedney, N., Cox, P. M., and Huntingford, C.: Climate feedback from wetland
methane emissions, Geophys. Res. Lett., 31, L20503.
https://doi.org/10.1029/2004GL020919, 2004.
Glumb, R., Davis, G., and Lietzke, C.: The TANSO-FTS-2 instrument for the
GOSAT-2 greenhouse gas monitoring mission, in: 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC, Canada, 13–18 July 2014, IEEE, 1238–1240, https://doi.org/10.1109/IGARSS.2014.6946656, 2014.
Green, R. O., Eastwood, M. L., Sarture, C. M., Chrien, T. G., Aronsson, M.,
Chippendale, B. J., Faust, J. A., Pavri, B. E., Chovit, C. J., Solis, M.,
Olah, M. R., and Williams, O.: Imaging spectroscopy and the Airborne
Visible/Infrared Imaging Spectrometer (AVIRIS), Remote Sens. Environ., 65,
227–248, https://doi.org/10.1016/S0034-4257(98)00064-9, 1998.
He, L., Zeng, Z.-C., Pongetti, T. J., Wong, C., Liang, J., Gurney, K. R.,
Newman, S., Yadav, V., Verhulst, K., Miller, C. E., and Duren, R.:
Atmospheric methane emissions correlate with natural gas consumption from
residential and commercial sectors in Los Angeles, Geophys. Res. Lett., 46,
8563–8571, https://doi.org/10.1029/2019GL083400, 2019.
Henyey, L. G. and Greenstein, J. L.: Diffuse radiation in the galaxy,
Astrophys. J., 93, 70–83, https://doi.org/10.1086/144246, 1941.
Herrero, M., Henderson, B., Havlík, P., Thornton, P. K., Conant, R. T., Smith, P., Wirsenius, S., Hristov, A. N., Gerber, P., Gill, M.,
Butterbach-Bahl, K., Valin, H., Garnett, T., and Shehfest, E.: Greenhouse
gas mitigation potentials in the livestock sector, Nat. Clim. Change, 6,
452–461, https://doi.org/10.1038/nclimate2925, 2016.
Holmes, C. D., Prather, M. J., Søvde, O. A., and Myhre, G.: Future methane, hydroxyl, and their uncertainties: key climate and emission parameters for future predictions, Atmos. Chem. Phys., 13, 285–302, https://doi.org/10.5194/acp-13-285-2013, 2013.
Howarth, R. W.: Methane emissions and climatic warming risk from hydraulic
fracturing and shale gas development: implications for policy, Energy and
Emission Control Technologies, 3, 45–54,
https://doi.org/10.2147/EECT.S61539, 2015.
Howarth, R. W.: Ideas and perspectives: is shale gas a major driver of recent increase in global atmospheric methane?, Biogeosciences, 16, 3033–3046, https://doi.org/10.5194/bg-16-3033-2019, 2019.
Howarth, R. W., Santoro, R., and Ingraffea, A.: Methane and the greenhouse
gas footprint of natural gas from shale formations, Clim. Change, 106, 679,
https://doi.org/10.1007/s10584-011-0061-5, 2011.
Jacob, D. J., Turner, A. J., Maasakkers, J. D., Sheng, J., Sun, K., Liu, X., Chance, K., Aben, I., McKeever, J., and Frankenberg, C.: Satellite observations of atmospheric methane and their value for quantifying methane emissions, Atmos. Chem. Phys., 16, 14371–14396, https://doi.org/10.5194/acp-16-14371-2016, 2016.
Jervis, D., McKeever, J., Durak, B. O. A., Sloan, J. J., Gains, D., Varon, D. J., Ramier, A., Strupler, M., and Tarrant, E.: The GHGSat-D imaging spectrometer, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-301, in review, 2020.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M.,
Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang,
J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR
40-year reanalysis project, B. Am. Meteorol. Soc., 77, 437–471,
https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
Kiemle, C., Kawa, S. R., Quatrevalet, M., and Browell, E. V.: Performance
simulations for a spaceborne methane lidar mission, J. Geophys. Res., 119,
4365–4379, https://doi.org/10.1002/2013JD021253, 2014.
Kirschke, S., Bousquet, P., Ciais, P., Saunois, M., Canadell, Josep G.,
Dlugokencky. E. J., Bergamaschi, P., Bergmann, D., Blake, D. R., Bruhwiler,
L., Cameron-Smith, P., Castaldi, S., Chevallier, F., Feng, L., Fraser, A.,
Heimann, M, Hodson, E. L., Houweling, S., Josse, B., Fraser, P. J., Krummel, P. B., Lamarque, J.-F., Langenfelds, R. L., Le Quere, C., Naik, V., O'Doherty, S., Palmer, P. I., Pison, I., Plummer, D., Poulter, B., Prinn, R. G., Rigby, M., Ringeval, B., Santini, M. Schmidt, M., Shindell, D. T., Simpson, I. J., Spahni, R., Steele, L. P., Strode, S. A., Sudo, K., Szopa, S., van der Werf, G. R., Voulgarakis, A., van Weele, M., Weiss, R. F., Williams, J. E., and Zeng, G.: Three decades of global methane sources and sinks, Nat. Geosci., 6, 813–823, https://doi.org/10.1038/ngeo1955, 2013.
Kort, E. A., Frankenberg, C., Costigan, K. R., Lindenmaier, R., Dubey, M.
K., and Wunch, D.: Four corners: the largest US methane anomaly viewed from
space, Geophys. Res. Lett., 41, 6898–6903,
https://doi.org/10.1002/2014GL061503, 2014.
Kuze, A., Suto, H., Shiomi, K., Kawakami, S., Tanaka, M., Ueda, Y., Deguchi, A., Yoshida, J., Yamamoto, Y., Kataoka, F., Taylor, T. E., and Buijs, H. L.: Update on GOSAT TANSO-FTS performance, operations, and data products after more than 6 years in space, Atmos. Meas. Tech., 9, 2445–2461, https://doi.org/10.5194/amt-9-2445-2016, 2016.
Kvenvolden, K. A.: Methane hydrate – A major reservoir of carbon in the
shallow geosphere?, Chem. Geol., 71, 41–51,
https://doi.org/10.1016/0009-2541(88)90104-0, 1988.
Kvenvolden, K. A. and Rogers, B. W.: Gaia's breath – global methane
exhalations, Mar. Petrol. Geol., 22, 579–590,
https://doi.org/10.1016/j.marpetgeo.2004.08.004, 2005.
Macdonald, J. A., Fowler, D., Hargreaves, K. J., Skiba, U., Leith, I. D.,
and Murray, M. B.: Methane emission rates from a northern wetland; response
to temperature, water table and transport, Atmos. Environ., 32, 3219–3227,
https://doi.org/10.1016/S1352-2310(97)00464-0, 1998.
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.
McKeever, J., Durak, B. O. A., Gains, D., Varon, D. J., Germain, S., and
Sloan, J. J.: GHGSat-D: Greenhouse gas plume imaging and quantification from space using a Fabry-Perot imaging spectrometer, 2017 Fall Meeting, AGU, New Orleans, LA, 11–15 December 2017, Abstract A33G-1360, 2017.
Merchant, C. J., Le Borgne, P., Roquet, H., and Legendre, G.: Extended
optimal estimation techniques for sea surface temperature from the Spinning
Enhanced Visible and Infra-Red Imager (SEVIRI), Remote Sens. Environ., 131,
287–297, https://doi.org/10.1016/j.rse.2012.12.019, 2013.
Myhre, G., Shindell, D., Bréon, F.-M., Collins, W., Fuglestvedt, J.,
Huang, J., Koch, D., Lamarque, J.-F., Lee, D., Mendoza, B., Nakajima, T.,
Robock, A., Stephens, G., Takemura, T., and Zhang, H.: Anthropogenic and Natural Radiative Forc-ing, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013.
Nisbet, E. G., Dlugokencky, E. J., and Bousquet, P.: Methane on the
rise–Again, Science, 343, 493–495, https://doi.org/10.1126/science.1247828, 2014.
Nisbet, E. G., Dlugokencky, E. J., Manning, M. R., Lowry, D., Fisher, R. E., France, J. L., Michel, S. E., Miller, J. B., White, J. W. C., Vaughn, B., Bousquet, P., Pyle, J. A., Warwick, N. J., Cain, M., Brownlow, R., Zazzeri, G., Lanoisellé, M., Manning, A. C., Gloor, E., Worthy, D. E. J., Brunke, E.-G., Labuschagne, C., Wolff, E. W., and Ganesan, A. L.: Rising atmospheric methane: 2007–2014 growth and isotopic shift, Global Biogeochem. Cy., 30, 1356–1370, https://doi.org/10.1002/2016GB005406, 2016.
NOAA/GML (NOAA Earth System Research Laboratory Global Monitoring Laboratory): Trends in Atmospheric Methane: Global CH4 Monthly Means, available at:
https://esrl.noaa.gov/gmd/ccgg/trends_ch4/, last access: 27 November 2020.
O'Dell, C. W., Eldering, A., Wennberg, P. O., Crisp, D., Gunson, M. R., Fisher, B., Frankenberg, C., Kiel, M., Lindqvist, H., Mandrake, L., Merrelli, A., Natraj, V., Nelson, R. R., Osterman, G. B., Payne, V. H., Taylor, T. E., Wunch, D., Drouin, B. J., Oyafuso, F., Chang, A., McDuffie, J., Smyth, M., Baker, D. F., Basu, S., Chevallier, F., Crowell, S. M. R., Feng, L., Palmer, P. I., Dubey, M., García, O. E., Griffith, D. W. T., Hase, F., Iraci, L. T., Kivi, R., Morino, I., Notholt, J., Ohyama, H., Petri, C., Roehl, C. M., Sha, M. K., Strong, K., Sussmann, R., Te, Y., Uchino, O., and Velazco, V. A.: Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm, Atmos. Meas. Tech., 11, 6539–6576, https://doi.org/10.5194/amt-11-6539-2018,
2018.
Polonsky, I. N., O'Brien, D. M., Kumer, J. B., O'Dell, C. W., and the geoCARB Team: Performance of a geostationary mission, geoCARB, to measure CO2, CH4 and CO column-averaged concentrations, Atmos. Meas. Tech., 7, 959–981, https://doi.org/10.5194/amt-7-959-2014, 2014.
Roberts, D. A., Bradley, E. S., Cheung, R., Leifer, I., Dennison, P. E., and Margolis, J. S.: Mapping methane emissions from a marine geological seep source using imaging spectrometry, Remote Sens. Environ., 114, 592–606, https://doi.org/10.1016/j.rse.2009.10.015, 2010.
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding: Theory and
Practice, World Scientific, Singapore, 2000.
Rothman, L. S., Gordon, I. E., Barbe, A., Benner, D. C., Bernath, P. E.,
Birk, M., Boudon, V., Brown, L. R., Campargue, A., Champion, J. P., Chance,
K., Coudert, L. H., Dana, V., Devi, V. M., Fally, S., Flaud, J. M., Gamache, R. R., Goldman, A., Jacquemart, D., Kleiner, I., Lacome, N., Lafferty, W. J., Mandin, J. Y., Massie, S. T., Mikhailenko, S. N., Miller, C. E., Moazzen-Ahmadi, N., Naumenko, O. V., Nikitin, A. V., Orphal, J., Perevalov, V. I., Perrin, A., Predoi-Cross, A., Rinsland, C. P., Rotger, M., Šimečková, M., Smith, M. A. H., Sung, K., Tashkun, S. A.,
Tennyson, J., Toth, R. A., Vandaele, A. C., and Vander Auwera, J.: The
HITRAN 2008 molecular spectroscopic database, J. Quant. Spectrosc. Ra., 110, 533–572, https://doi.org/10.1016/j.jqsrt.2009.02.013, 2009.
Schaefer, H., Fletcher, S. E. M., Veidt, C., Lassey, K. R., Brailsford, G.
W., Bromley, T. M., Dlugokencky, E. J., Michel, S. E., Miller, J. M., Levin, I., Lowe, D. C., Martin, R. J., Vaughn, B. H., and White, J. W. C.: A 21st-century shift from fossil-fuel to biogenic methane emissions indicated by 13CH4, Science, 352, 80–84,
https://doi.org/10.1126/science.aad2705, 2016.
Schaefer, K., Lantuit, H., Romanovsky, V. E., Schuur, E. A. G., and Witt,
R.: The impact of the permafrost carbon feedback on global climate, Environ. Res. Lett., 9, 085003, https://doi.org/10.1088/1748-9326/9/8/085003, 2014.
Schuur, E. A. G., McGuire, A. D., Schädel, C., Grosse, G., Harden, J.
W., Hayes, D. J., Hugelius, G., Koven, C. D., Kuhry, P., Lawrence, D. M.,
Natali, S. M., Olefeldt, D., Romanovsky, V. E., Schaefer, K., Turetsky, M.
R., Treat, C. C., and Vonk, J. E.: Climate change and the permafrost carbon
feedback, Nature, 520, 171–179, https://doi.org/10.1038/nature14338, 2015.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: From
Air Pollution to Climate Change, Wiley, New Jersey, USA, 2006.
Spurr, R. and Natraj, V.: A linearized two-stream radiative transfer code
for fast approximation of multiple-scatter fields, J. Quant. Spectrosc.
Ra., 112, 2630–2637, https://doi.org/10.1016/j.jqsrt.2011.06.014, 2011.
Themelis, N. J. and Ulloa, P. A.: Methane generation in landfills,
Renewable Energy, 32, 1243–1257, https://doi.org/10.1016/j.renene.2006.04.020, 2007.
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.
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.
Thorpe, A. K., Frankenberg, C., and Roberts, D. A.: Retrieval techniques for airborne imaging of methane concentrations using high spatial and moderate spectral resolution: application to AVIRIS, Atmos. Meas. Tech., 7, 491–506, https://doi.org/10.5194/amt-7-491-201, 2014.
Varon, D. J., McKeever, J., Jervis, D., Maasakkers, J. D., Pandey, S.,
Houweling, S., Aben, I., Scarpelli, T., and Jacob, D. J.: Satellite discovery of anomalously large methane point sources from oil/gas production, Geophys. Res. Lett., 46, 13507–13516, https://doi.org/10.1029/2019GL083798, 2019.
Veefkind, J. P., Aben, I., McMullan, K., Forster, H., de Vries, J.,Otter,
G., Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele, M.,
Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann, P.,
Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.: TROPOMI
on the ESA Sentinel-5 Precursor: A GMES mission for global observations of
the atmospheric composition for climate, air quality and ozone layer
applications, Remote Sens. Environ., 120, 70–83,
https://doi.org/10.1016/j.rse.2011.09.027, 2012.
Walter, K. M., Zimov, S. A., Chanton, J. P., Verbyla, D., and Chapin III, F. S.: Methane bubbling from Siberian thaw lakes as a positive feedback to
climate warming, Nature, 443, 71–75, https://doi.org/10.1038/nature05040, 2006.
WCRP (World Climate Research Program): A preliminary cloudless standard
atmosphere for radiation computation, International Association for
Meteorology and Atmospheric Physics, Radiation Commission, Boulder, CO, USA, WMO/TD-No. 24; WCP-No. 112, March 1986.
Wofsy, S. C. and Hamburg, S: MethaneSAT – A new observing platform for
high resolution measurements of methane and carbon dioxide, 2019 Fall Meeting, AGU, San Francisco, CA, 9–13 December 2019, Abstract A53F-02, 2019.
Woodwell, G. M., Mackenzie, F. T., Houghton, R. A., Apps, M., Gorham, E.,
and Davidson, E.: Biotic feedbacks in the warming of the earth, Climatic
Change, 40, 495–518, https://doi.org/10.1023/A:1005345429236, 1998.
Worden, J., Kulawik, S., Frankenberg, C., Payne, V., Bowman, K., Cady-Peirara, K., Wecht, K., Lee, J.-E., and Noone, D.: Profiles of CH4, HDO, H2O, and N2O with improved lower tropospheric vertical resolution from Aura TES radiances, Atmos. Meas. Tech., 5, 397–411, https://doi.org/10.5194/amt-5-397-2012, 2012.
Xi, X., Natraj, V., Shia, R. L., Luo, M., Zhang, Q., Newman, S., Sander, S. P., and Yung, Y. L.: Simulated retrievals for the remote sensing of CO2, CH4, CO, and H2O from geostationary orbit, Atmos. Meas. Tech., 8, 4817–4830, https://doi.org/10.5194/amt-8-4817-2015, 2015.
Xiong, X., Barnet, C., Maddy, E., Sweeney, C., Liu, X., Zhou, L., and
Goldberg, M.: Characterization and validation of methane products from the
Atmospheric Infrared Sounder (AIRS), J. Geophys. Res., 113, G00A01,
https://doi.org/10.1029/2007JG000500, 2008.
Xiong, X., Barnet, C., Maddy, E. S., Gambacorta, A., King, T. S., and Wofsy, S. C.: Mid-upper tropospheric methane retrieval from IASI and its validation, Atmos. Meas. Tech., 6, 2255–2265, https://doi.org/10.5194/amt-6-2255-2013, 2013.
Yoshida, Y., Kikuchi, N., Morino, I., Uchino, O., Oshchepkov, S., Bril, A., Saeki, T., Schutgens, N., Toon, G. C., Wunch, D., Roehl, C. M., Wennberg, P. O., Griffith, D. W. T., Deutscher, N. M., Warneke, T., Notholt, J., Robinson, J., Sherlock, V., Connor, B., Rettinger, M., Sussmann, R., Ahonen, P., Heikkinen, P., Kyrö, E., Mendonca, J., Strong, K., Hase, F., Dohe, S., and Yokota, T.: Improvement of the retrieval algorithm for GOSAT SWIR XCO2 and XCH4 and their validation using TCCON data, Atmos. Meas. Tech., 6, 1533–1547, https://doi.org/10.5194/amt-6-1533-2013, 2013.
Zeng, Z.-C., Zhang, Q., Natraj, V., Margolis, J. S., Shia, R.-L., Newman, S., Fu, D., Pongetti, T. J., Wong, K. W., Sander, S. P., Wennberg, P. O., and Yung, Y. L.: Aerosol scattering effects on water vapor retrievals over the Los Angeles Basin, Atmos. Chem. Phys., 17, 2495–2508, https://doi.org/10.5194/acp-17-2495-2017, 2017.
Zeng, Z.-C., Natraj, V., Xu, F., Pongetti, T. J., Shia, R.-L., Kort, E. A.,
Toon, G. C., Sander, S. P., and Yung, Y. L.: Constraining aerosol vertical
profile in the boundary layer using hyperspectral measurements of oxygen
absorption, Geophys. Res. Lett., 45, 10772–10780,
https://doi.org/10.1029/2018GL079286, 2018.
Zhang, Q., Natraj, V., Li, K.-F., Shia, R.-L., Fu, D., Pongetti, T. J., Sander S. P., Roehl, C. M., and Yung, Y. L.: Accounting for aerosol
scattering in the CLARS retrieval of column averaged CO2 mixing ratios, J. Geophys. Res.-Atmos., 120, 7205–7218, https://doi.org/10.1002/2015JD023499, 2015.
Zhang, Q., Shia, R. -L., Sander, S. P., and Yung, Y. L.: XCO2 retrieval error over deserts near critical surface albedo, Earth Space Sci., 2, 1–10, https://doi.org/10.1002/2015EA000143, 2016.
Short summary
As a greenhouse gas with strong global warming potential, atmospheric methane emissions have attracted a great deal of attention. However, accurate assessment of these emissions is challenging in the presence of atmospheric particulates called aerosols. We quantify the aerosol impact on methane quantification from airborne measurements using two techniques, one that has traditionally been used by the imaging spectroscopy community and the other commonly employed in trace gas remote sensing.
As a greenhouse gas with strong global warming potential, atmospheric methane emissions have...