Articles | Volume 12, issue 3
https://doi.org/10.5194/amt-12-1495-2019
© Author(s) 2019. 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-12-1495-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Mar 2019
Research article |
| 07 Mar 2019
| 07 Mar 2019
The impact of improved aerosol priors on near-infrared measurements of carbon dioxide
Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA
Christopher W. O'Dell
Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
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Revised manuscript accepted for AMT
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Emily Bell, Christopher W. O'Dell, Thomas E. Taylor, Aronne Merrelli, Robert R. Nelson, Matthäus Kiel, Annmarie Eldering, Robert Rosenberg, and Brendan Fisher
Atmos. Meas. Tech., 16, 109–133, https://doi.org/10.5194/amt-16-109-2023, https://doi.org/10.5194/amt-16-109-2023, 2023
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Hélène Peiro, Sean Crowell, Andrew Schuh, David F. Baker, Chris O'Dell, Andrew R. Jacobson, Frédéric Chevallier, Junjie Liu, Annmarie Eldering, David Crisp, Feng Deng, Brad Weir, Sourish Basu, Matthew S. Johnson, Sajeev Philip, and Ian Baker
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Michael Buchwitz, Maximilian Reuter, Stefan Noël, Klaus Bramstedt, Oliver Schneising, Michael Hilker, Blanca Fuentes Andrade, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Hartmut Boesch, Lianghai Wu, Jochen Landgraf, Ilse Aben, Christian Retscher, Christopher W. O'Dell, and David Crisp
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Steven T. Massie, Heather Cronk, Aronne Merrelli, Christopher O'Dell, K. Sebastian Schmidt, Hong Chen, and David Baker
Atmos. Meas. Tech., 14, 1475–1499, https://doi.org/10.5194/amt-14-1475-2021, https://doi.org/10.5194/amt-14-1475-2021, 2021
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The OCO-2 science team is working to retrieve CO2 measurements that can be used by the carbon cycle community to calculate regional sources and sinks of CO2. The retrieved data, however, are in need of improvements in accuracy. This paper discusses several ways in which 3D cloud metrics (such as the distance of a measurement to the nearest cloud) can be used to account for cloud effects in the OCO-2 CO2 data files.
Robert R. Nelson, Annmarie Eldering, David Crisp, Aronne J. Merrelli, and Christopher W. O'Dell
Atmos. Meas. Tech., 13, 6889–6899, https://doi.org/10.5194/amt-13-6889-2020, https://doi.org/10.5194/amt-13-6889-2020, 2020
Short summary
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Measurements of surface wind speed over oceans are scientifically useful. Here we show that the Orbiting Carbon Observatory-2 (OCO-2), originally designed to measure carbon dioxide using reflected sunlight, can also accurately and precisely measure wind speed. OCO-2's high spatial resolution means that it can observe close to coastlines and therefore be used to study coastal wind processes and inform related economic sectors.
Nicole Jacobs, William R. Simpson, Debra Wunch, Christopher W. O'Dell, Gregory B. Osterman, Frank Hase, Thomas Blumenstock, Qiansi Tu, Matthias Frey, Manvendra K. Dubey, Harrison A. Parker, Rigel Kivi, and Pauli Heikkinen
Atmos. Meas. Tech., 13, 5033–5063, https://doi.org/10.5194/amt-13-5033-2020, https://doi.org/10.5194/amt-13-5033-2020, 2020
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The boreal forest is the largest seasonally varying biospheric CO2-exchange region on Earth. This region is also undergoing amplified climate warming, leading to concerns about the potential for altered regional carbon exchange. Satellite missions, such as the Orbiting Carbon Observatory-2 (OCO-2) project, can measure CO2 abundance over the boreal forest but need validation for the assurance of accuracy. Therefore, we carried out a ground-based validation of OCO-2 CO2 data at three locations.
Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Stefan Noël, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Antonio Di Noia, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Lianghai Wu, Otto P. Hasekamp, Ilse Aben, Akihiko Kuze, Hiroshi Suto, Kei Shiomi, Yukio Yoshida, Isamu Morino, David Crisp, Christopher W. O'Dell, Justus Notholt, Christof Petri, Thorsten Warneke, Voltaire A. Velazco, Nicholas M. Deutscher, David W. T. Griffith, Rigel Kivi, David F. Pollard, Frank Hase, Ralf Sussmann, Yao V. Té, Kimberly Strong, Sébastien Roche, Mahesh K. Sha, Martine De Mazière, Dietrich G. Feist, Laura T. Iraci, Coleen M. Roehl, Christian Retscher, and Dinand Schepers
Atmos. Meas. Tech., 13, 789–819, https://doi.org/10.5194/amt-13-789-2020, https://doi.org/10.5194/amt-13-789-2020, 2020
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We present new satellite-derived data sets of atmospheric carbon dioxide (CO2) and methane (CH4). The data products are column-averaged dry-air mole fractions of CO2 and CH4, denoted XCO2 and XCH4. The products cover the years 2003–2018 and are merged Level 2 (satellite footprints) and merged Level 3 (gridded at monthly time and 5° x 5° spatial resolution) products obtained from combining several individual sensor products. We present the merging algorithms and product validation results.
Susan S. Kulawik, Chris O'Dell, Robert R. Nelson, and Thomas E. Taylor
Atmos. Meas. Tech., 12, 5317–5334, https://doi.org/10.5194/amt-12-5317-2019, https://doi.org/10.5194/amt-12-5317-2019, 2019
Short summary
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This work investigates errors in CO2 near-infrared estimates retrieved from simulated radiances. We find that interferent errors are underpredicted and that nonlinearity causes significant errors.
Sean Crowell, David Baker, Andrew Schuh, Sourish Basu, Andrew R. Jacobson, Frederic Chevallier, Junjie Liu, Feng Deng, Liang Feng, Kathryn McKain, Abhishek Chatterjee, John B. Miller, Britton B. Stephens, Annmarie Eldering, David Crisp, David Schimel, Ray Nassar, Christopher W. O'Dell, Tomohiro Oda, Colm Sweeney, Paul I. Palmer, and Dylan B. A. Jones
Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, https://doi.org/10.5194/acp-19-9797-2019, 2019
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Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network. We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 (OCO-2) show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.
Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Sven Krautwurst, Christopher W. O'Dell, Andreas Richter, Heinrich Bovensmann, and John P. Burrows
Atmos. Chem. Phys., 19, 9371–9383, https://doi.org/10.5194/acp-19-9371-2019, https://doi.org/10.5194/acp-19-9371-2019, 2019
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The quantification of anthropogenic emissions with current CO2 satellite sensors is difficult, but NO2 is co-emitted, making it a suitable tracer of recently emitted CO2. We analyze enhancements of CO2 and NO2 observed by OCO-2 and S5P and estimate the CO2 plume cross-sectional fluxes that we compare with emission databases. Our results demonstrate the usefulness of simultaneous satellite observations of CO2 and NO2 as envisaged for the European Copernicus anthropogenic CO2 monitoring mission
Annmarie Eldering, Thomas E. Taylor, Christopher W. O'Dell, and Ryan Pavlick
Atmos. Meas. Tech., 12, 2341–2370, https://doi.org/10.5194/amt-12-2341-2019, https://doi.org/10.5194/amt-12-2341-2019, 2019
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NASA's Orbiting Carbon Observatory-3 (OCO-3) is scheduled for a 2019 launch to the International Space Station (ISS). It is expected to continue the record of column carbon dioxide (XCO2) and solar-induced chlorophyll fluorescence (SIF) measurements from space used to study and constrain the Earth's carbon cycle. This work highlights the measurement objectives and uses simulated data to show that the expected instrument performance is on par with that of OCO-2.
Matthäus Kiel, Christopher W. O'Dell, Brendan Fisher, Annmarie Eldering, Ray Nassar, Cameron G. MacDonald, and Paul O. Wennberg
Atmos. Meas. Tech., 12, 2241–2259, https://doi.org/10.5194/amt-12-2241-2019, https://doi.org/10.5194/amt-12-2241-2019, 2019
Christopher W. O'Dell, Annmarie Eldering, Paul O. Wennberg, David Crisp, Michael R. Gunson, Brendan Fisher, Christian Frankenberg, Matthäus Kiel, Hannakaisa Lindqvist, Lukas Mandrake, Aronne Merrelli, Vijay Natraj, Robert R. Nelson, Gregory B. Osterman, Vivienne H. Payne, Thomas E. Taylor, Debra Wunch, Brian J. Drouin, Fabiano Oyafuso, Albert Chang, James McDuffie, Michael Smyth, David F. Baker, Sourish Basu, Frédéric Chevallier, Sean M. R. Crowell, Liang Feng, Paul I. Palmer, Mavendra Dubey, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, Hirofumi Ohyama, Christof Petri, Coleen M. Roehl, Mahesh K. Sha, Kimberly Strong, Ralf Sussmann, Yao Te, Osamu Uchino, and Voltaire A. Velazco
Atmos. Meas. Tech., 11, 6539–6576, https://doi.org/10.5194/amt-11-6539-2018, https://doi.org/10.5194/amt-11-6539-2018, 2018
Michael Buchwitz, Maximilian Reuter, Oliver Schneising, Stefan Noël, Bettina Gier, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Rob G. Detmers, Otto P. Hasekamp, Ilse Aben, André Butz, Akihiko Kuze, Hiroshi Suto, Yukio Yoshida, David Crisp, and Christopher O'Dell
Atmos. Chem. Phys., 18, 17355–17370, https://doi.org/10.5194/acp-18-17355-2018, https://doi.org/10.5194/acp-18-17355-2018, 2018
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We present a new satellite data set of column-averaged mixing ratios of carbon dioxide (CO2), which covers the time period 2003 to 2016. We used this data set to compute annual mean atmospheric CO2 growth rates. We show that the growth rate is highest during 2015 and 2016 despite nearly constant CO2 emissions from fossil fuel burning in recent years. The high growth rates are attributed to year 2015-2016 El Nino episodes. We present correlations with fossil fuel emissions and ENSO indices.
David Crisp, Harold R. Pollock, Robert Rosenberg, Lars Chapsky, Richard A. M. Lee, Fabiano A. Oyafuso, Christian Frankenberg, Christopher W. O'Dell, Carol J. Bruegge, Gary B. Doran, Annmarie Eldering, Brendan M. Fisher, Dejian Fu, Michael R. Gunson, Lukas Mandrake, Gregory B. Osterman, Florian M. Schwandner, Kang Sun, Tommy E. Taylor, Paul O. Wennberg, and Debra Wunch
Atmos. Meas. Tech., 10, 59–81, https://doi.org/10.5194/amt-10-59-2017, https://doi.org/10.5194/amt-10-59-2017, 2017
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The Orbiting Carbon Observatory-2 carries and points a three-channel imaging grating spectrometer designed to collect high-resolution spectra of reflected sunlight within the molecular oxygen A-band at 0.765 microns and the carbon dioxide bands at 1.61 and 2.06 microns. Here, we describe the OCO-2 instrument, its data products, and its performance during its first 18 months in orbit.
Brian Connor, Hartmut Bösch, James McDuffie, Tommy Taylor, Dejian Fu, Christian Frankenberg, Chris O'Dell, Vivienne H. Payne, Michael Gunson, Randy Pollock, Jonathan Hobbs, Fabiano Oyafuso, and Yibo Jiang
Atmos. Meas. Tech., 9, 5227–5238, https://doi.org/10.5194/amt-9-5227-2016, https://doi.org/10.5194/amt-9-5227-2016, 2016
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We present an analysis of uncertainties in global measurements of the column-averaged dry-air mole fraction of CO2 (XCO2) by the satellite OCO-2. The analysis is based on our best estimates for uncertainties in the OCO-2 operational algorithm and its inputs. From these results we estimate the "variable error", which differs between soundings, to infer the error in the difference of XCO2 between any two soundings. Variable errors are usually < 1 ppm over ocean and ~ 0.5–2 ppm over land.
Robert R. Nelson, Christopher W. O'Dell, Thomas E. Taylor, Lukas Mandrake, and Mike Smyth
Atmos. Meas. Tech., 9, 1671–1684, https://doi.org/10.5194/amt-9-1671-2016, https://doi.org/10.5194/amt-9-1671-2016, 2016
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In this work, we test the hypothesis that clear-sky retrievals may perform as well as full-physics retrievals for very clear scenes. It was found that for simulated OCO-2 measurements, the clear-sky retrieval had errors comparable to those of the full-physics retrieval. For real GOSAT data, the clear-sky retrieval had errors 0–20 % larger than the full-physics retrieval over land and 20–35 % larger over ocean. This work implies that clear-sky retrievals may be more useful than previously assumed.
Thomas E. Taylor, Christopher W. O'Dell, Christian Frankenberg, Philip T. Partain, Heather Q. Cronk, Andrey Savtchenko, Robert R. Nelson, Emily J. Rosenthal, Albert Y. Chang, Brenden Fisher, Gregory B. Osterman, Randy H. Pollock, David Crisp, Annmarie Eldering, and Michael R. Gunson
Atmos. Meas. Tech., 9, 973–989, https://doi.org/10.5194/amt-9-973-2016, https://doi.org/10.5194/amt-9-973-2016, 2016
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NASA's Orbiting Carbon Observatory-2 (OCO-2) is providing approximately 1 million soundings per day of the total column of carbon dioxide (XCO2). The retrieval of XCO2 can only be performed for soundings sufficiently free of cloud and aerosol. This work highlights comparisons of OCO-2 cloud screening algorithms to the MODIS cloud mask product. We find agreement approximately 85 % of the time with some significant spatial and small seasonal dependencies.
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
In-flight estimation of instrument spectral response functions using sparse representations
Robustness of atmospheric trace gas retrievals obtained from low-spectral-resolution Fourier transform infrared absorption spectra under variations of interferogram length
Retrieval of NO2 profiles from 3 years of Pandora MAX-DOAS measurements in Toronto, Canada
A channel selection methodology for enhancing volcanic SO2 monitoring using FY-3E/HIRAS-II hyperspectral data
Predictions of failed satellite retrieval of air quality using machine learning
Deep transfer learning method for seasonal TROPOMI XCH4 albedo correction
Global retrieval of TROPOMI tropospheric HCHO and NO2 columns with improved consistency based on the updated Peking University OMI NO2 algorithm
Quantitative estimate of several sources of uncertainty in drone-based methane emission measurements
Implementation and application of an improved phase spectrum determination scheme for Fourier transform spectrometry
Remote sensing of lower-middle-thermosphere temperatures using the N2 Lyman–Birge–Hopfield (LBH) bands
Retrievals of water vapour and temperature exploiting the far-infrared: application to aircraft observations in preparation for the FORUM mission
Global decadal measurements of methanol, ethene, ethyne, and HCN from the Cross-track Infrared Sounder
Forward model emulator for atmospheric radiative transfer using Gaussian processes and cross validation
Developments on a 22 GHz microwave radiometer and reprocessing of 13-year time series for water vapour studies
Optimal selection of satellite XCO2 images for urban CO2 emission monitoring
Separating and quantifying facility-level methane emissions with overlapping plumes for spaceborne methane monitoring
A study of measurement scenarios for the future CO2M mission: avoidance of detector saturation and the impact on XCO2 retrievals
Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks
Surface reflectance biases in XCH4 retrievals from the 2.3 μm band are enhanced in the presence of aerosols
Remote sensing of methane point sources with the MethaneAIR airborne spectrometer
The differences between remote sensing and in situ air pollutant measurements over the Canadian oil sands
NitroNet – a machine learning model for the prediction of tropospheric NO2 profiles from TROPOMI observations
Improved convective cloud differential (CCD) tropospheric ozone from S5P-TROPOMI satellite data using local cloud fields
Atmospheric propane (C3H8) column retrievals from ground-based FTIR observations in Xianghe, China
Hourly surface nitrogen dioxide retrieval from GEMS tropospheric vertical column densities: Benefit of using time-contiguous input features for machine learning models
Can the remote sensing of combustion phase improve estimates of landscape fire smoke emission rate and composition?
Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS
Troposphere–stratosphere-integrated bromine monoxide (BrO) profile retrieval over the central Pacific Ocean
Local and regional enhancements of CH4, CO, and CO2 inferred from TCCON column measurements
Merging TEMPEST microwave and GOES-16 geostationary IR soundings for improved water vapor profiles
Remote Sensing Estimates of Time-Resolved HONO and NO2 Emission Rates and Lifetimes in Wildfires
Assimilation of volcanic sulfur dioxide products from IASI and TROPOMI into the chemical transport model MOCAGE: case study of the 2021 La Soufrière Saint-Vincent eruption
Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission
Mapping the CO2 total column retrieval performance from shortwave infrared measurements: synthetic impacts of the spectral resolution, signal-to-noise ratio, and spectral band selection
Assessment of the contribution of the Meteosat Third Generation Infrared Sounder (MTG-IRS) for the characterisation of ozone over Europe
Assessing the potential of free-tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events
Current potential of CH4 emission estimates using TROPOMI in the Middle East
A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument
Estimation of biogenic volatile organic compound (BVOC) emissions in forest ecosystems using drone-based lidar, photogrammetry, and image recognition technologies
Fast retrieval of XCO2 over east Asia based on Orbiting Carbon Observatory-2 (OCO-2) spectral measurements
A new method for estimating megacity NOx emissions and lifetimes from satellite observations
Accounting for the effect of aerosols in GHGSat methane retrieval
A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B
Global retrieval of stratospheric and tropospheric BrO columns from the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on board the Suomi-NPP satellite
IMK–IAA MIPAS retrieval version 8: CH4 and N2O
Report on Landsat 8 and Sentinel-2B observations of the Nord Stream 2 pipeline methane leak
U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers
CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates
Quantitative imaging of carbon dioxide plumes using a ground-based shortwave infrared spectral camera
Jihanne El Haouari, Jean-Michel Gaucel, Christelle Pittet, Jean-Yves Tourneret, and Herwig Wendt
Atmos. Meas. Tech., 18, 2573–2590, https://doi.org/10.5194/amt-18-2573-2025, https://doi.org/10.5194/amt-18-2573-2025, 2025
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This paper explores new techniques based on sparse representations for estimating the spectral response functions of high-resolution spectrometers. The method is highly competitive, with commonly used parametric models yielding more accurate estimates while accounting for wavelength dependence. The resulting normalized estimation errors of the spectrometer spectral responses are less than 1 %, which will allow for better quantification of trace gas concentrations at the Earth surface.
Bavo Langerock, Martine De Mazière, Filip Desmet, Pauli Heikkinen, Rigel Kivi, Mahesh Kumar Sha, Corinne Vigouroux, Minqiang Zhou, Gopala Krishna Darbha, and Mohmmed Talib
Atmos. Meas. Tech., 18, 2439–2446, https://doi.org/10.5194/amt-18-2439-2025, https://doi.org/10.5194/amt-18-2439-2025, 2025
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Ground-based Fourier transform interferometer instruments have been used for many decades to measure direct solar light in the infrared to obtain high-resolution spectra from which atmospheric gas profile concentrations can be derived. It is shown that the typical processing chain used to derive atmospheric gas columns can be sensitive to relatively small shortenings of the recorded interferograms. Low-resolution recordings, used in more recent years, are more sensitive to such adaptations.
Ramina Alwarda, Kristof Bognar, Xiaoyi Zhao, Vitali Fioletov, Jonathan Davies, Sum Chi Lee, Debora Griffin, Alexandru Lupu, Udo Frieß, Alexander Cede, Yushan Su, and Kimberly Strong
Atmos. Meas. Tech., 18, 2397–2423, https://doi.org/10.5194/amt-18-2397-2025, https://doi.org/10.5194/amt-18-2397-2025, 2025
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Nitrogen dioxide (NO2) is a pollutant with a short lifetime and large variability, but there are limited measurements of its distribution in the lower atmosphere. We present a new 3-year dataset of NO2 vertical profiles in Toronto, Canada, and evaluate it using NO2 from satellite and surface monitoring networks and simulations by an air quality forecast model. We quantify and explain the differences among the datasets to provide information that can be used to understand NO2 variability.
Xinyu Li, Lin Zhu, Hongfu Sun, Jun Li, Ximing Lv, Chengli Qi, and Huanhuan Yan
Atmos. Meas. Tech., 18, 2333–2352, https://doi.org/10.5194/amt-18-2333-2025, https://doi.org/10.5194/amt-18-2333-2025, 2025
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This paper proposes a novel methodology for selecting sulfur-dioxide-sensitive channels from FY-3E/HIRAS-II hyperspectral IR atmospheric sensors to quantitatively monitor volcanic sulfur dioxide. This methodology considers the interference of atmospheric temperature, humidity, and surface temperature with sulfur dioxide detection and retrieval, laying the groundwork for developing a more accurate and flexible volcanic sulfur dioxide retrieval algorithm under different atmospheric conditions.
Edward Malina, Jure Brence, Jennifer Adams, Jovan Tanevski, Sašo Džeroski, Valentin Kantchev, and Kevin W. Bowman
Atmos. Meas. Tech., 18, 1689–1715, https://doi.org/10.5194/amt-18-1689-2025, https://doi.org/10.5194/amt-18-1689-2025, 2025
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The large fleet of Earth observation satellites in orbit currently generate huge volumes of data, requiring significant computational resources to process these data in a timely manner. We present a method for predicting poor-quality measurements using machine learning. We find that machine learning methods can accurately predict poor-quality measurements and remove them from the processing chain, saving time and computational resources.
Alexander C. Bradley, Barbara Dix, Fergus Mackenzie, J. Pepijn Veefkind, and Joost A. de Gouw
Atmos. Meas. Tech., 18, 1675–1687, https://doi.org/10.5194/amt-18-1675-2025, https://doi.org/10.5194/amt-18-1675-2025, 2025
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Currently, measurement of methane from the TROPOMI satellite is biased with respect to surface reflectance. This study demonstrates a new method of correcting for this bias on a seasonal timescale to allow for differences in surface reflectance in areas of intense agriculture where growing seasons may introduce a reflectance bias. We have successfully implemented this technique in the Denver–Julesburg basin, where agriculture and methane extraction infrastructure is often co-located.
Yuhang Zhang, Huan Yu, Isabelle De Smedt, Jintai Lin, Nicolas Theys, Michel Van Roozendael, Gaia Pinardi, Steven Compernolle, Ruijing Ni, Fangxuan Ren, Sijie Wang, Lulu Chen, Jos Van Geffen, Mengyao Liu, Alexander M. Cede, Martin Tiefengraber, Alexis Merlaud, Martina M. Friedrich, Andreas Richter, Ankie Piters, Vinod Kumar, Vinayak Sinha, Thomas Wagner, Yongjoo Choi, Hisahiro Takashima, Yugo Kanaya, Hitoshi Irie, Robert Spurr, Wenfu Sun, and Lorenzo Fabris
Atmos. Meas. Tech., 18, 1561–1589, https://doi.org/10.5194/amt-18-1561-2025, https://doi.org/10.5194/amt-18-1561-2025, 2025
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We developed an advanced algorithm for global retrieval of TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO2 vertical column densities with much improved consistency. Sensitivity tests demonstrate the complexity and nonlinear interactions of auxiliary parameters in the air mass factor calculation. An improved agreement is found with measurements from a global ground-based instrument network. The scientific retrieval provides a useful source of information for studies combining HCHO and NO2.
Tannaz H. Mohammadloo, Matthew Jones, Bas van de Kerkhof, Kyle Dawson, Brendan J. Smith, Stephen Conley, Abigail Corbett, and Rutger IJzermans
Atmos. Meas. Tech., 18, 1301–1324, https://doi.org/10.5194/amt-18-1301-2025, https://doi.org/10.5194/amt-18-1301-2025, 2025
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Methane is a potent greenhouse gas. Trustable detection and quantification of methane emissions at facility level are critical for identifying the largest sources and prioritizing them for repair. We provide a systematic analysis of several sources of uncertainty in drone-based methane emission surveys based on theoretical considerations and historical data sets. We provide guidelines for industry on how to avoid or minimize errors in drone-based methane emission quantification surveys.
Frank Hase, Paolo Castracane, Angelika Dehn, Omaira Elena García, David W. T. Griffith, Lukas Heizmann, Nicholas B. Jones, Tomi Karppinen, Rigel Kivi, Martine de Mazière, Justus Notholt, and Mahesh Kumar Sha
Atmos. Meas. Tech., 18, 1257–1267, https://doi.org/10.5194/amt-18-1257-2025, https://doi.org/10.5194/amt-18-1257-2025, 2025
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The primary measurement result delivered by a Fourier transform spectrometer is an interferogram, and the spectrum required for further analysis needs to be calculated from the interferogram by Fourier analysis. The paper deals with technical aspects of this process and shows how the reconstruction of the spectrum can be optimized.
Richard Eastes, J. Scott Evans, Quan Gan, William McClintock, and Jerry Lumpe
Atmos. Meas. Tech., 18, 921–928, https://doi.org/10.5194/amt-18-921-2025, https://doi.org/10.5194/amt-18-921-2025, 2025
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Temperature is essential to understanding the thermosphere. Most temperature measurements have been indirect or had large uncertainties, especially in the lower-middle thermosphere, where data are rarely available. Since October 2018, NASA’s GOLD mission has produced disk images of neutral temperatures near 160 km at locations over the Americas and Atlantic Ocean. This paper discusses both temperature retrieval techniques and issues in interpreting GOLD’s images of thermospheric temperatures.
Sanjeevani Panditharatne, Helen Brindley, Caroline Cox, Richard Siddans, Jonathan Murray, Laura Warwick, and Stuart Fox
Atmos. Meas. Tech., 18, 717–735, https://doi.org/10.5194/amt-18-717-2025, https://doi.org/10.5194/amt-18-717-2025, 2025
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Observations from the upcoming European Space Agency’s Far-Infrared Outgoing Radiation Understanding and Monitoring (FORUM) satellite are theorised to be highly sensitive to distributions of water vapour within Earth’s atmosphere. We exploit this sensitivity and extend the Infrared Microwave Sounding retrieval scheme for use on observations from FORUM. This scheme is evaluated on both simulated and observed measurements and shows good agreement with references of the atmospheric state.
Kelley C. Wells, Dylan B. Millet, Jared F. Brewer, Vivienne H. Payne, Karen E. Cady-Pereira, Rick Pernak, Susan Kulawik, Corinne Vigouroux, Nicholas Jones, Emmanuel Mahieu, Maria Makarova, Tomoo Nagahama, Ivan Ortega, Mathias Palm, Kimberly Strong, Matthias Schneider, Dan Smale, Ralf Sussmann, and Minqiang Zhou
Atmos. Meas. Tech., 18, 695–716, https://doi.org/10.5194/amt-18-695-2025, https://doi.org/10.5194/amt-18-695-2025, 2025
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Atmospheric volatile organic compounds (VOCs) affect both air quality and climate. Satellite measurements can help us to assess and predict their global impacts. We present new decadal (2012–2023) measurements of four key VOCs – methanol, ethene, ethyne, and hydrogen cyanide (HCN) – from the Cross-track Infrared Sounder. The measurements reflect emissions from major forests, wildfires, and industry and provide new information to advance understanding of these sources and their changes over time.
Otto Lamminpää, Jouni Susiluoto, Jonathan Hobbs, James McDuffie, Amy Braverman, and Houman Owhadi
Atmos. Meas. Tech., 18, 673–694, https://doi.org/10.5194/amt-18-673-2025, https://doi.org/10.5194/amt-18-673-2025, 2025
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We develop and demonstrate a fast forward function emulator for remote sensing of greenhouse gases. These forward functions are computationally expensive to evaluate, and as such the key challenge for many satellite missions in their data processing is the time used in these evaluations. Our method is fast and accurate enough, less than 1 % relative error, so that it could be safely used in operational processing.
Alistair Bell, Eric Sauvageat, Gunter Stober, Klemens Hocke, and Axel Murk
Atmos. Meas. Tech., 18, 555–567, https://doi.org/10.5194/amt-18-555-2025, https://doi.org/10.5194/amt-18-555-2025, 2025
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Hardware and software developments have been made on a 22 GHz microwave radiometer for the measurement of middle-atmospheric water vapour near Bern, Switzerland. Previous measurements dating back to 2010 have been re-calibrated and an improved optimal estimation retrieval performed on these measurements, giving a 13-year dataset. Measurements made with new and improved instrumental hardware are used to correct previous measurements, which show better agreement than the non-corrected dataset.
Alexandre Danjou, Grégoire Broquet, Andrew Schuh, François-Marie Bréon, and Thomas Lauvaux
Atmos. Meas. Tech., 18, 533–554, https://doi.org/10.5194/amt-18-533-2025, https://doi.org/10.5194/amt-18-533-2025, 2025
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We study the capacity of XCO2 spaceborne imagery to estimate urban CO2 emissions with synthetic data. We define automatic and standard methods and objective criteria for image selection. The wind variability and urban emission budget guide the emission estimation error. Images with low wind variability and high urban emissions account for 47 % of images and give a bias in the emission estimation of −7 % and a spread of 56 %. Other images give a bias of −31 % and a spread of 99 %.
Yiguo Pang, Longfei Tian, Denghui Hu, Shuang Gao, and Guohua Liu
Atmos. Meas. Tech., 18, 455–470, https://doi.org/10.5194/amt-18-455-2025, https://doi.org/10.5194/amt-18-455-2025, 2025
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The spatial adjacency of methane point sources can result in plume overlapping, presenting challenges for quantification from space. A separation and quantification method combining the Gaussian plume model and the integrated mass enhancement method is proposed. A modern parameter estimation technique is introduced to separate the overlapping plumes from satellite observations. The proposed method is evaluated with synthesized observations and real satellite observations.
Michael Weimer, Michael Hilker, Stefan Noël, Max Reuter, Michael Buchwitz, Blanca Fuentes Andrade, Rüdiger Lang, Bernd Sierk, Yasjka Meijer, Heinrich Bovensmann, John P. Burrows, and Hartmut Bösch
EGUsphere, https://doi.org/10.5194/egusphere-2024-3857, https://doi.org/10.5194/egusphere-2024-3857, 2025
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Optical detectors have a maximum signal (saturation). Exceedance means that the measurement has to be discarded. We investigate where saturation will occur for the future European satellite mission dedicated to CO2 Monitoring (CO2M) and strategies to avoid saturation. It impacts coverage and precision, both important for estimation of local CO2 emissions. We find that taking two pictures per sampling should be sufficient to avoid saturation for CO2M with some impact on the CO2 precision.
Maximilian Reuter, Michael Hilker, Stefan Noël, Antonio Di Noia, Michael Weimer, Oliver Schneising, Michael Buchwitz, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 18, 241–264, https://doi.org/10.5194/amt-18-241-2025, https://doi.org/10.5194/amt-18-241-2025, 2025
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Carbon dioxide (CO2) and methane (CH4) are the main anthropogenic greenhouse gases. The European Copernicus CO2 monitoring satellite mission CO2M will provide measurements of their atmospheric concentrations, but the accuracy requirements are demanding and conventional retrieval methods computationally expensive. We present a new retrieval algorithm based on artificial neural networks that has the potential to meet the stringent requirements of the CO2M mission with minimal computational effort.
Peter Somkuti, Greg M. McGarragh, Christopher O'Dell, Antonio Di Noia, Leif Vogel, Sean Crowell, Lesley E. Ott, and Hartmut Bösch
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-145, https://doi.org/10.5194/amt-2024-145, 2025
Revised manuscript accepted for AMT
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In space-based estimates of atmospheric methane concentrations, one can often observe biases that look like imprints of surface features. We performed realistic simulation experiments and find the root cause to be unaccounted aerosols. Since good knowledge of aerosols is difficult to achieve for operational science data processing, we conclude that a comprehensive surface bias correction scheme is highly important for missions utilizing the 2.3 µm spectral band for methane retrievals.
Luis Guanter, Jack Warren, Mark Omara, Apisada Chulakadabba, Javier Roger, Maryann Sargent, Jonathan E. Franklin, Steven C. Wofsy, and Ritesh Gautam
EGUsphere, https://doi.org/10.5194/egusphere-2024-3577, https://doi.org/10.5194/egusphere-2024-3577, 2025
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This study presents a data processing scheme for the detection and quantification of methane emissions using the MethaneAIR airborne spectrometer. We show that the proposed methods enable the detection of smaller plumes than other existing methods, and that improves the potential of MethaneAIR to survey methane point sources across large regions
Xiaoyi Zhao, Vitali Fioletov, Debora Griffin, Chris McLinden, Ralf Staebler, Cristian Mihele, Kevin Strawbridge, Jonathan Davies, Ihab Abboud, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, and Robert Swap
Atmos. Meas. Tech., 17, 6889–6912, https://doi.org/10.5194/amt-17-6889-2024, https://doi.org/10.5194/amt-17-6889-2024, 2024
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This study explores differences between remote sensing and in situ instruments in terms of their vertical, horizontal, and temporal sampling differences. Understanding and resolving these differences are critical for future analyses linking satellite, ground-based remote sensing, and in situ observations in air quality monitoring. It shows that the meteorological conditions (wind directions, speed, and boundary layer conditions) will strongly affect the agreement between the two measurements.
Leon Kuhn, Steffen Beirle, Sergey Osipov, Andrea Pozzer, and Thomas Wagner
Atmos. Meas. Tech., 17, 6485–6516, https://doi.org/10.5194/amt-17-6485-2024, https://doi.org/10.5194/amt-17-6485-2024, 2024
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This paper presents a new machine learning model that allows us to compute NO2 concentration profiles from satellite observations. A neural network was trained on synthetic data from the regional chemistry and transport model WRF-Chem. This is the first model of its kind. We present a thorough model validation study, covering various seasons and regions of the world.
Swathi Maratt Satheesan, Kai-Uwe Eichmann, John P. Burrows, Mark Weber, Ryan Stauffer, Anne M. Thompson, and Debra Kollonige
Atmos. Meas. Tech., 17, 6459–6484, https://doi.org/10.5194/amt-17-6459-2024, https://doi.org/10.5194/amt-17-6459-2024, 2024
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CHORA, an advanced cloud convective differential technique, enhances the accuracy of tropospheric-ozone retrievals. Unlike the traditional Pacific cloud reference sector scheme, CHORA introduces a local-cloud reference sector and an alternative approach (CLCT) for precision. Analysing monthly averaged TROPOMI data from 2018 to 2022 and validating with SHADOZ ozonesonde data, CLCT outperforms other methods and so is the preferred choice, especially in future geostationary satellite missions.
Minqiang Zhou, Pucai Wang, Bart Dils, Bavo Langerock, Geoff Toon, Christian Hermans, Weidong Nan, Qun Cheng, and Martine De Mazière
Atmos. Meas. Tech., 17, 6385–6396, https://doi.org/10.5194/amt-17-6385-2024, https://doi.org/10.5194/amt-17-6385-2024, 2024
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Solar absorption spectra near 2967 cm−1 recorded by a ground-based FTIR with a high spectral resolution of 0.0035 cm-1 are applied to retrieve C3H8 columns for the first time in Xianghe, China, within the NDACC-IRWG. The mean and standard deviation of the C3H8 columns are 1.80 ± 0.81 (1σ) × 1015 molec. cm-2. Good correlations are found between C3H8 and other non-methane hydrocarbons, such as C2H6 (R = 0.84) and C2H2 (R = 0.79), as well as between C3H8 and CO (R = 0.72).
Janek Gödeke, Andreas Richter, Kezia Lange, Peter Maaß, Hyunkee Hong, Hanlim Lee, and Junsung Park
EGUsphere, https://doi.org/10.5194/egusphere-2024-3145, https://doi.org/10.5194/egusphere-2024-3145, 2024
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The Korean Geostationary Environmental Monitoring Spectrometer (GEMS) monitors trace gases over Asia, e.g., NO2. GEMS provides hourly data, improving the time-resolution compared to the daily overpasses by other satellites. For the prediction of hourly surface NO2 over Korea from GEMS observations and meteorological data, this study shows that machine learning models benefit from this higher time-resolution. This is achieved by using observations from previous hours as additional inputs.
Farrer Owsley-Brown, Martin J. Wooster, Mark J. Grosvenor, and Yanan Liu
Atmos. Meas. Tech., 17, 6247–6264, https://doi.org/10.5194/amt-17-6247-2024, https://doi.org/10.5194/amt-17-6247-2024, 2024
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Landscape fires produce vast amounts of smoke, affecting the atmosphere locally and globally. Whether a fire is flaming or smouldering strongly impacts the rate at which smoke is produced as well as its composition. This study tested two methods to determine these combustion phases in laboratory fires and compared them to the smoke emitted. One of these methods improved estimates of smoke emission significantly. This suggests potential for improvement in global emission estimates.
Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Víctor Molina García, Diego Loyola, Hanlim Lee, and Jhoon Kim
Atmos. Meas. Tech., 17, 6163–6191, https://doi.org/10.5194/amt-17-6163-2024, https://doi.org/10.5194/amt-17-6163-2024, 2024
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In this study, we developed an advanced retrieval algorithm for tropospheric NO2 columns from geostationary satellite spectrometers and applied it to GEMS measurements. The DLR GEMS NO2 retrieval algorithm follows the heritage from previous and existing algorithms, but improved approaches are applied to reflect the specific features of geostationary satellites. The DLR GEMS NO2 retrievals demonstrate a good capability for monitoring diurnal variability with a high spatial resolution.
Theodore K. Koenig, François Hendrick, Douglas Kinnison, Christopher F. Lee, Michel Van Roozendael, and Rainer Volkamer
Atmos. Meas. Tech., 17, 5911–5934, https://doi.org/10.5194/amt-17-5911-2024, https://doi.org/10.5194/amt-17-5911-2024, 2024
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Atmospheric bromine destroys ozone, impacts oxidation capacity, and oxidizes mercury into its toxic form. We constrain bromine by remote sensing of BrO from a mountaintop. Previous measurements retrieved two to three pieces of information vertically; we apply new methods to get five and a half vertically and two more in time. We compare with aircraft measurements to validate the methods and look at variations in BrO over the Pacific.
Kavitha Mottungan, Chayan Roychoudhury, Vanessa Brocchi, Benjamin Gaubert, Wenfu Tang, Mohammad Amin Mirrezaei, John McKinnon, Yafang Guo, David W. T. Griffith, Dietrich G. Feist, Isamu Morino, Mahesh K. Sha, Manvendra K. Dubey, Martine De Mazière, Nicholas M. Deutscher, Paul O. Wennberg, Ralf Sussmann, Rigel Kivi, Tae-Young Goo, Voltaire A. Velazco, Wei Wang, and Avelino F. Arellano Jr.
Atmos. Meas. Tech., 17, 5861–5885, https://doi.org/10.5194/amt-17-5861-2024, https://doi.org/10.5194/amt-17-5861-2024, 2024
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A combination of data analysis techniques is introduced to separate local and regional influences on observed levels of carbon dioxide, carbon monoxide, and methane from an established ground-based remote sensing network. We take advantage of the covariations in these trace gases to identify the dominant type of sources driving these levels. Applying these methods in conjunction with existing approaches to other datasets can better address uncertainties in identifying sources and sinks.
Chia-Pang Kuo and Christian Kummerow
Atmos. Meas. Tech., 17, 5637–5653, https://doi.org/10.5194/amt-17-5637-2024, https://doi.org/10.5194/amt-17-5637-2024, 2024
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A small satellite about the size of a shoe box, named TEMPEST, carries only a microwave sensor and is designed to measure the water cycle of the Earth from space in an economical way compared with traditional satellites, which have additional infrared sensors. To overcome the limitation, extra infrared signals from GOES-R ABI are combined with TEMPEST microwave measurements. Compared with ground observations, improved humidity information is extracted from the merged TEMPEST and ABI signals.
Carley D. Fredrickson, Scott J. Janz, Lok N. Lamsal, Ursula A. Jongebloed, Joshua L. Laughner, and Joel A. Thornton
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-158, https://doi.org/10.5194/amt-2024-158, 2024
Revised manuscript accepted for AMT
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We present an analysis of high-resolution remote sensing measurements of nitrogen-containing trace gases emitted by wildfires. The measurements were made using an instrument on the NASA ER-2 aircraft in the summer of 2019. We find that time-resolved fire intensity is critical to quantify trace gas emissions over a fire’s entire lifespan. These findings have implications for improving air pollution forecasts downwind of wildfires using computer models of atmospheric chemistry and meteorology.
Mickaël Bacles, Jonathan Améric, and Vincent Guidard
EGUsphere, https://doi.org/10.5194/egusphere-2024-2941, https://doi.org/10.5194/egusphere-2024-2941, 2024
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Sulfur dioxide emitted during volcanic eruptions can be hazardous for aviation safety. A recent development aims at improving the forecasts of volcanic sulfur dioxide quantities made by the MOCAGE chemistry transport model. Both TROPOMI and IASI instruments are assimilated in the model. We focus on the eruption event of the La Soufrière Saint-Vincent volcano in April 2021. The combined assimilation of IASI and TROPOMI observations always leads to a better analyses and forecasts.
Christopher Chan Miller, Sébastien Roche, Jonas S. Wilzewski, Xiong Liu, Kelly Chance, Amir H. Souri, Eamon Conway, Bingkun Luo, Jenna Samra, Jacob Hawthorne, Kang Sun, Carly Staebell, Apisada Chulakadabba, Maryann Sargent, Joshua S. Benmergui, Jonathan E. Franklin, Bruce C. Daube, Yang Li, Joshua L. Laughner, Bianca C. Baier, Ritesh Gautam, Mark Omara, and Steven C. Wofsy
Atmos. Meas. Tech., 17, 5429–5454, https://doi.org/10.5194/amt-17-5429-2024, https://doi.org/10.5194/amt-17-5429-2024, 2024
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MethaneSAT is an upcoming satellite mission designed to monitor methane emissions from the oil and gas (O&G) industry globally. Here, we present observations from the first flight campaign of MethaneAIR, a MethaneSAT-like instrument mounted on an aircraft. MethaneAIR can map methane with high precision and accuracy over a typically sized oil and gas basin (~200 km2) in a single flight. This paper demonstrates the capability of the upcoming satellite to routinely track global O&G emissions.
Matthieu Dogniaux and Cyril Crevoisier
Atmos. Meas. Tech., 17, 5373–5396, https://doi.org/10.5194/amt-17-5373-2024, https://doi.org/10.5194/amt-17-5373-2024, 2024
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Many CO2-observing satellite concepts, with very different design choices and trade-offs, are expected to be put into orbit during the upcoming decade. This work uses numerical simulations to explore the impact of critical design parameters on the performance of upcoming CO2-observing satellite concepts.
Francesca Vittorioso, Vincent Guidard, and Nadia Fourrié
Atmos. Meas. Tech., 17, 5279–5299, https://doi.org/10.5194/amt-17-5279-2024, https://doi.org/10.5194/amt-17-5279-2024, 2024
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The future Meteosat Third Generation Infrared Sounder (MTG-IRS) will represent a major innovation for the monitoring of the chemical state of the atmosphere. MTG-IRS will have the advantage of being based on a geostationary platform and acquiring data with a high temporal frequency. This work aims to evaluate its potential impact over Europe within a chemical transport model (MOCAGE). The results indicate that the assimilation of these data always has a positive impact on ozone analysis.
Matthias Schneider, Kinya Toride, Farahnaz Khosrawi, Frank Hase, Benjamin Ertl, Christopher J. Diekmann, and Kei Yoshimura
Atmos. Meas. Tech., 17, 5243–5259, https://doi.org/10.5194/amt-17-5243-2024, https://doi.org/10.5194/amt-17-5243-2024, 2024
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Despite its importance for extreme weather and climate feedbacks, atmospheric convection is not well constrained. This study assesses the potential of novel tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events. We find that the impact of the isotopologues is small for stable atmospheric conditions but significant for unstable conditions, which have the strongest societal impacts (e.g. storms and flooding).
Mengyao Liu, Ronald van der A, Michiel van Weele, Lotte Bryan, Henk Eskes, Pepijn Veefkind, Yongxue Liu, Xiaojuan Lin, Jos de Laat, and Jieying Ding
Atmos. Meas. Tech., 17, 5261–5277, https://doi.org/10.5194/amt-17-5261-2024, https://doi.org/10.5194/amt-17-5261-2024, 2024
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A new divergence method was developed and applied to estimate methane emissions from TROPOMI observations over the Middle East, where it is typically challenging for a satellite to measure methane due to its complicated orography and surface albedo. Our results show the potential of TROPOMI to quantify methane emissions from various sources rather than big emitters from space after objectively excluding the artifacts in the retrieval.
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, https://doi.org/10.5194/amt-17-5147-2024, 2024
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We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
Xianzhong Duan, Ming Chang, Guotong Wu, Suping Situ, Shengjie Zhu, Qi Zhang, Yibo Huangfu, Weiwen Wang, Weihua Chen, Bin Yuan, and Xuemei Wang
Atmos. Meas. Tech., 17, 4065–4079, https://doi.org/10.5194/amt-17-4065-2024, https://doi.org/10.5194/amt-17-4065-2024, 2024
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Accurately estimating biogenic volatile organic compound (BVOC) emissions in forest ecosystems has been challenging. This research presents a framework that utilizes drone-based lidar, photogrammetry, and image recognition technologies to identify plant species and estimate BVOC emissions. The largest cumulative isoprene emissions were found in the Myrtaceae family, while those of monoterpenes were from the Rubiaceae family.
Fengxin Xie, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang, Kei Shiomi, and Isamu Morino
Atmos. Meas. Tech., 17, 3949–3967, https://doi.org/10.5194/amt-17-3949-2024, https://doi.org/10.5194/amt-17-3949-2024, 2024
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This study demonstrates a new machine learning approach to efficiently and accurately estimate atmospheric carbon dioxide levels from satellite data. Rather than using traditional complex physics-based retrieval methods, neural network models are trained on simulated data to rapidly predict CO2 concentrations directly from satellite spectral measurements.
Steffen Beirle and Thomas Wagner
Atmos. Meas. Tech., 17, 3439–3453, https://doi.org/10.5194/amt-17-3439-2024, https://doi.org/10.5194/amt-17-3439-2024, 2024
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We present a new method for estimating emissions and lifetimes for nitrogen oxides emitted from large cities by using satellite NO2 observations combined with wind fields. The estimate is based on the simultaneous evaluation of the downwind plumes for opposing wind directions. This allows us to derive seasonal mean emissions and lifetimes for 100 cities around the globe.
Qiurun Yu, Dylan Jervis, and Yi Huang
Atmos. Meas. Tech., 17, 3347–3366, https://doi.org/10.5194/amt-17-3347-2024, https://doi.org/10.5194/amt-17-3347-2024, 2024
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This study estimated the effects of aerosols on GHGSat satellite methane retrieval and investigated the performance of simultaneously retrieving aerosol and methane information using a multi-angle viewing method. Results suggested that the performance of GHGSat methane retrieval improved when aerosols were considered, and the multi-angle viewing method is insensitive to the satellite angle setting. This performance assessment is useful for improving future GHGSat-like instruments.
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
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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.
Heesung Chong, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Alfonso Saiz-Lopez, Rafael P. Fernandez, Hyeong-Ahn Kwon, Zolal Ayazpour, Huiqun Wang, Amir H. Souri, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Jhoon Kim, Ja-Ho Koo, William R. Simpson, François Hendrick, Richard Querel, Glen Jaross, Colin Seftor, and Raid M. Suleiman
Atmos. Meas. Tech., 17, 2873–2916, https://doi.org/10.5194/amt-17-2873-2024, https://doi.org/10.5194/amt-17-2873-2024, 2024
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We present a new bromine monoxide (BrO) product derived using radiances measured from OMPS-NM on board the Suomi-NPP satellite. This product provides nearly a decade of global stratospheric and tropospheric column retrievals, a feature that is currently rare in publicly accessible datasets. Both stratospheric and tropospheric columns from OMPS-NM demonstrate robust performance, exhibiting good agreement with ground-based observations collected at three stations (Lauder, Utqiagvik, and Harestua).
Norbert Glatthor, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 17, 2849–2871, https://doi.org/10.5194/amt-17-2849-2024, https://doi.org/10.5194/amt-17-2849-2024, 2024
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We present global atmospheric methane (CH4) and nitrous oxide (N2O) distributions retrieved from measurements of the MIPAS instrument on board the Environmental Satellite (Envisat) during 2002 to 2012. Monitoring of these gases is of scientific interest because both of them are strong greenhouse gases. We analyze the latest, improved version of calibrated MIPAS measurements. Further, we apply a new retrieval scheme leading to an improved CH4 and N2O data product .
Matthieu Dogniaux, Joannes D. Maasakkers, Daniel J. Varon, and Ilse Aben
Atmos. Meas. Tech., 17, 2777–2787, https://doi.org/10.5194/amt-17-2777-2024, https://doi.org/10.5194/amt-17-2777-2024, 2024
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We analyze Landsat 8 (L8) and Sentinel-2B (S-2B) observations of the 2022 Nord Stream 2 methane leak and show how challenging this case is for usual data analysis methods. We provide customized calibrations for this Nord Stream 2 case and assess that no firm conclusion can be drawn from L8 or S-2B single overpasses. However, if we opportunistically assume that L8 and S-2B results are independent, we find an averaged L8 and S-2B combined methane leak rate of 502 ± 464 t h−1.
Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob
Atmos. Meas. Tech., 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, https://doi.org/10.5194/amt-17-2625-2024, 2024
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Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.
Anna Vaughan, Gonzalo Mateo-García, Luis Gómez-Chova, Vít Růžička, Luis Guanter, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 2583–2593, https://doi.org/10.5194/amt-17-2583-2024, https://doi.org/10.5194/amt-17-2583-2024, 2024
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Methane is a potent greenhouse gas that has been responsible for around 25 % of global warming since the industrial revolution. Consequently identifying and mitigating methane emissions comprise an important step in combating the climate crisis. We develop a new deep learning model to automatically detect methane plumes from satellite images and demonstrate that this can be applied to monitor large methane emissions resulting from the oil and gas industry.
Stefan Noël, Michael Buchwitz, Michael Hilker, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 17, 2317–2334, https://doi.org/10.5194/amt-17-2317-2024, https://doi.org/10.5194/amt-17-2317-2024, 2024
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FOCAL-CO2M is one of the three operational retrieval algorithms which will be used to derive XCO2 and XCH4 from measurements of the forthcoming European CO2M mission. We present results of applications of FOCAL-CO2M to simulated spectra, from which confidence is gained that the algorithm is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).
Marvin Knapp, Ralph Kleinschek, Sanam N. Vardag, Felix Külheim, Helge Haveresch, Moritz Sindram, Tim Siegel, Bruno Burger, and André Butz
Atmos. Meas. Tech., 17, 2257–2275, https://doi.org/10.5194/amt-17-2257-2024, https://doi.org/10.5194/amt-17-2257-2024, 2024
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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.
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Short summary
Accurate measurements of carbon dioxide are essential when studying climate change. In this work, we try to improve measurements of carbon dioxide from the Orbiting Carbon Observatory-2 by using better informed aerosol priors from an atmospheric model. We find that this makes the carbon dioxide measurements slightly more accurate and that certain ways of using modeled aerosol information are more promising than others.
Accurate measurements of carbon dioxide are essential when studying climate change. In this...
