Articles | Volume 17, issue 21
https://doi.org/10.5194/amt-17-6385-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-6385-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Nov 2024
Research article |
| 06 Nov 2024
| 06 Nov 2024
Atmospheric propane (C3H8) column retrievals from ground-based FTIR observations in Xianghe, China
Minqiang Zhou
CORRESPONDING AUTHOR
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Pucai Wang
CORRESPONDING AUTHOR
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
Institute of Carbon Neutrality, Qilu Zhongke, Jinan, China
Bart Dils
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
Bavo Langerock
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
Geoff Toon
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Christian Hermans
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
Weidong Nan
Xianghe Observatory of Whole Atmosphere, Institute of Atmospheric Physics, Chinese Academy of Sciences, Xianghe, China
Qun Cheng
Xianghe Observatory of Whole Atmosphere, Institute of Atmospheric Physics, Chinese Academy of Sciences, Xianghe, China
Martine De Mazière
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
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The seasonal evolution of O3 and its photochemical production regime in a polluted region of eastern China between 2014 and 2017 was investigated using FTS observations. We observed a broad summer O3 maximum in Hefei, China, and the ozone production is mainly NOx limited in spring and summer and is mainly VOC or mixed VOC–NOx limited in autumn and winter.
Minqiang Zhou, Bavo Langerock, Corinne Vigouroux, Mahesh Kumar Sha, Michel Ramonet, Marc Delmotte, Emmanuel Mahieu, Whitney Bader, Christian Hermans, Nicolas Kumps, Jean-Marc Metzger, Valentin Duflot, Zhiting Wang, Mathias Palm, and Martine De Mazière
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Minqiang Zhou, Bavo Langerock, Corinne Vigouroux, Pucai Wang, Christian Hermans, Gabriele Stiller, Kaley A. Walker, Geoff Dutton, Emmanuel Mahieu, and Martine De Mazière
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Profiles of CFC-11, CFC-12 and HCFC-22 have been obtained from FTIR measurements above the Saint-Denis and Maïdo sites at Reunion Island (21° S, 55° E) with low vertical resolution. The trends derived from the FTIR measurements are −0.86 ± 0.12 % and 2.84 ± 0.06 % for CFC-11 and HCFC-22, respectively, for the period 2004 to 2016, and −0.76 ± 0.05 % for CFC-12 for 2009 to 2016, which are consistent with ground-based in situ observations. Our FTIR data and the collocated MIPAS data are in good agreement.
Minqiang Zhou, Bart Dils, Pucai Wang, Rob Detmers, Yukio Yoshida, Christopher W. O'Dell, Dietrich G. Feist, Voltaire Almario Velazco, Matthias Schneider, and Martine De Mazière
Atmos. Meas. Tech., 9, 1415–1430, https://doi.org/10.5194/amt-9-1415-2016, https://doi.org/10.5194/amt-9-1415-2016, 2016
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The sun-glint XCO2 and XCH4 products (“ocean data”) of thermal and near infrared sensor for carbon observations Fourier transform spectrometer (TANSO-FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) from several retrieval algorithms is compared with the FTIR measurements form near-ocean Total Carbon Column Observing Network (TCCON) sites, and the results indicate that the ocean data show a good agreement with TCCON measurements.
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.
Pengfei Han, Ning Zeng, Bo Yao, Wen Zhang, Weijun Quan, Pucai Wang, Ting Wang, Minqiang Zhou, Qixiang Cai, Yuzhong Zhang, Ruosi Liang, Wanqi Sun, and Shengxiang Liu
Atmos. Chem. Phys., 25, 4965–4988, https://doi.org/10.5194/acp-25-4965-2025, https://doi.org/10.5194/acp-25-4965-2025, 2025
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Methane (CH4) is a potent greenhouse gas. Northern China contributes a large proportion of CH4 emissions, yet large observation gaps exist. Here we compiled a comprehensive dataset, which is publicly available, that includes ground-based, satellite-based, inventory, and modeling results to show the CH4 concentrations, enhancements, and spatial–temporal variations. The data can benefit the research community and policy-makers for future observations, atmospheric inversions, and policy-making.
Andrew Gerald Barr, Jochen Landgraf, Mari Martinez-Velarte, Mihalis Vrekoussis, Ralf Sussmann, Isamu Morino, Kimberly Strong, Minqiang Zhou, Voltaire A. Velazco, Hirofumi Ohyama, Thorsten Warneke, Frank Hase, and Tobias Borsdorff
EGUsphere, https://doi.org/10.5194/egusphere-2024-3990, https://doi.org/10.5194/egusphere-2024-3990, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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In 2019 GOSAT-2 was launched, to realise the second in a series of satellites dedicated to measuring concentrations of greenhouse gases from space. The datasets obtained from GOSAT-2 are used in the Copernicus atmospheric services to monitor the climate, in light of the Paris Agreement. Over the five years the increase of CH4 and CO2 concentration in the atmosphere is clear. Here we present three robust datasets from GOSAT-2, including a novel machine learning approach to data quality filtering.
Ying Zhou, Congcong Qiao, Minqiang Zhou, Yilong Wang, Xiangjun Tian, Yinghong Wang, and Minzheng Duan
Atmos. Meas. Tech., 18, 1609–1619, https://doi.org/10.5194/amt-18-1609-2025, https://doi.org/10.5194/amt-18-1609-2025, 2025
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We developed an automated, flexible atmospheric sampling device for various platforms. During a 5 d field campaign in the Mount Qomolangma region, we performed 15 flights using the device mounted on a hexacopter unoccupied aerial vehicle (UAV). A total of 139 samples were analyzed using an Agilent 7890A gas chromatograph. Vertical profiles of four greenhouse gases (carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and sulfur hexafluoride (SF6)) were analyzed and discussed.
Minqiang Zhou, Yilong Wang, Minzheng Duan, Xiangjun Tian, Jinzhi Ding, Jianrong Bi, Yaoming Ma, Weiqiang Ma, and Zhenhua Xi
EGUsphere, https://doi.org/10.5194/egusphere-2025-1293, https://doi.org/10.5194/egusphere-2025-1293, 2025
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The Qinghai-Tibetan Plateau is a key system that impacts the global carbon balance. This study presents the greenhouse gas (GHG) mole fraction measurement campaign in May 2022 at Mt. Qomolangma station, including ground-based remote sensing and in situ measurements. The GHG measurements are carried out in this region for the first time and used for satellite validation.
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.
Amir H. Souri, Gonzalo González Abad, Glenn M. Wolfe, Tijl Verhoelst, Corinne Vigouroux, Gaia Pinardi, Steven Compernolle, Bavo Langerock, Bryan N. Duncan, and Matthew S. Johnson
Atmos. Chem. Phys., 25, 2061–2086, https://doi.org/10.5194/acp-25-2061-2025, https://doi.org/10.5194/acp-25-2061-2025, 2025
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We establish a simple yet robust relationship between ozone production rates and geophysical parameters obtained from several intensive atmospheric composition campaigns. We show that satellite remote sensing data can effectively constrain these parameters, enabling us to produce the first global maps of ozone production rates with unprecedented resolution.
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.
Aki Tsuruta, Akihiko Kuze, Kei Shiomi, Fumie Kataoka, Nobuhiro Kikuchi, Tuula Aalto, Leif Backman, Ella Kivimäki, Maria K. Tenkanen, Kathryn McKain, Omaira E. García, Frank Hase, Rigel Kivi, Isamu Morino, Hirofumi Ohyama, David F. Pollard, Mahesh K. Sha, Kimberly Strong, Ralf Sussmann, Yao Te, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, Minqiang Zhou, and Hiroshi Suto
EGUsphere, https://doi.org/10.5194/egusphere-2025-159, https://doi.org/10.5194/egusphere-2025-159, 2025
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Satellite data bring invaluable information about greenhouse gas emissions globally. We found that a new type of data from the Greenhouse Gas Observing Satellite (GOSAT), which contains information about methane in the lowest layer of Earth's atmosphere, could provide reliable estimates of recent methane emissions when combined with atmospheric modelling. Therefore, the use of such data is encouraged to improve emission quantification methods and advance our understanding of methane cycles.
Robin Björklund, Corinne Vigouroux, Peter Effertz, Omaira E. García, Alex Geddes, James Hannigan, Koji Miyagawa, Michael Kotkamp, Bavo Langerock, Gerald Nedoluha, Ivan Ortega, Irina Petropavlovskikh, Deniz Poyraz, Richard Querel, John Robinson, Hisako Shiona, Dan Smale, Penny Smale, Roeland Van Malderen, and Martine De Mazière
Atmos. Meas. Tech., 17, 6819–6849, https://doi.org/10.5194/amt-17-6819-2024, https://doi.org/10.5194/amt-17-6819-2024, 2024
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Different ground-based ozone measurements from the last 2 decades at Lauder are compared to each other. We want to know why different trends have been observed in the stratosphere. Also, the quality and relevance of tropospheric datasets need to be evaluated. While remaining drifts are still present, our study explains roughly half of the differences in observed trends in previous studies and shows the necessity for continuous review and improvement of the measurements.
Sieglinde Callewaert, Minqiang Zhou, Bavo Langerock, Pucai Wang, Ting Wang, Emmanuel Mahieu, and Martine De Mazière
EGUsphere, https://doi.org/10.5194/egusphere-2024-3228, https://doi.org/10.5194/egusphere-2024-3228, 2024
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We used an atmospheric transport model and satellite data to study CH4 observations at Xianghe, China. Our study shows the key source sectors that influence the concentrations and their respective importance. Furthermore, meteorological factors such as wind direction are discussed. This research highlights the challenges in accurately simulating these kind of measurements and helps us to better understand CH4 variability in the region.
Maggie Bruckner, R. Bradley Pierce, Allen Lenzen, Glenn Diskin, Josh DiGangi, Martine De Maziere, Nicholas Jones, and Maria Makarova
EGUsphere, https://doi.org/10.5194/egusphere-2024-2501, https://doi.org/10.5194/egusphere-2024-2501, 2024
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UFS-RAQMS incorporates the Real-time Air Quality Modeling System (RAQMS) stratosphere/troposphere chemistry into the existing NOAA Global Ensemble Forecast System (GEFS-Aerosol) version of NOAA's Unified Forecast System (UFS). Chemical data assimilation using TROPOMI CO column observations is conducted during the July-August-September 2019 period. Comparison of CO column with independent measurements shows a systematic low bias in biomass burning CO emissions without assimilation.
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.
Bart Dils, Minqiang Zhou, Claude Camy-Peyret, Martine De Mazière, Yannick Kangah, Bavo Langerock, Pascal Prunet, Carmine Serio, Richard Siddans, and Brian Kerridge
Atmos. Meas. Tech., 17, 5491–5524, https://doi.org/10.5194/amt-17-5491-2024, https://doi.org/10.5194/amt-17-5491-2024, 2024
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The paper discusses two very distinct methane products from the IASI instrument aboard the MetOp-A satellite. One (referred to as LMD NLISv8.3) uses a machine-learning approach, while the other (RALv2.0) uses a more conventional optimal estimation approach. We used a variety of model and independent reference measurement data to assess both products' overall quality, their differences, and specific aspects of each product that would benefit from further analysis by the product development teams.
Henk Eskes, Athanasios Tsikerdekis, Melanie Ades, Mihai Alexe, Anna Carlin Benedictow, Yasmine Bennouna, Lewis Blake, Idir Bouarar, Simon Chabrillat, Richard Engelen, Quentin Errera, Johannes Flemming, Sebastien Garrigues, Jan Griesfeller, Vincent Huijnen, Luka Ilić, Antje Inness, John Kapsomenakis, Zak Kipling, Bavo Langerock, Augustin Mortier, Mark Parrington, Isabelle Pison, Mikko Pitkänen, Samuel Remy, Andreas Richter, Anja Schoenhardt, Michael Schulz, Valerie Thouret, Thorsten Warneke, Christos Zerefos, and Vincent-Henri Peuch
Atmos. Chem. Phys., 24, 9475–9514, https://doi.org/10.5194/acp-24-9475-2024, https://doi.org/10.5194/acp-24-9475-2024, 2024
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The Copernicus Atmosphere Monitoring Service (CAMS) provides global analyses and forecasts of aerosols and trace gases in the atmosphere. On 27 June 2023 a major upgrade, Cy48R1, became operational. Comparisons with in situ, surface remote sensing, aircraft, and balloon and satellite observations show that the new CAMS system is a significant improvement. The results quantify the skill of CAMS to forecast impactful events, such as wildfires, dust storms and air pollution peaks.
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.
Joshua L. Laughner, Geoffrey C. Toon, Joseph Mendonca, Christof Petri, Sébastien Roche, Debra Wunch, Jean-Francois Blavier, David W. T. Griffith, Pauli Heikkinen, Ralph F. Keeling, Matthäus Kiel, Rigel Kivi, Coleen M. Roehl, Britton B. Stephens, Bianca C. Baier, Huilin Chen, Yonghoon Choi, Nicholas M. Deutscher, Joshua P. DiGangi, Jochen Gross, Benedikt Herkommer, Pascal Jeseck, Thomas Laemmel, Xin Lan, Erin McGee, Kathryn McKain, John Miller, Isamu Morino, Justus Notholt, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Haris Riris, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Steven C. Wofsy, Minqiang Zhou, and Paul O. Wennberg
Earth Syst. Sci. Data, 16, 2197–2260, https://doi.org/10.5194/essd-16-2197-2024, https://doi.org/10.5194/essd-16-2197-2024, 2024
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This paper describes a new version, called GGG2020, of a data set containing column-integrated observations of greenhouse and related gases (including CO2, CH4, CO, and N2O) made by ground stations located around the world. Compared to the previous version (GGG2014), improvements have been made toward site-to-site consistency. This data set plays a key role in validating space-based greenhouse gas observations and in understanding the carbon cycle.
Felicia Kolonjari, Patrick E. Sheese, Kaley A. Walker, Chris D. Boone, David A. Plummer, Andreas Engel, Stephen A. Montzka, David E. Oram, Tanja Schuck, Gabriele P. Stiller, and Geoffrey C. Toon
Atmos. Meas. Tech., 17, 2429–2449, https://doi.org/10.5194/amt-17-2429-2024, https://doi.org/10.5194/amt-17-2429-2024, 2024
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The Canadian Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) satellite instrument is currently providing the only vertically resolved chlorodifluoromethane (HCFC-22) measurements from space. This study assesses the most current ACE-FTS HCFC-22 data product in the upper troposphere and lower stratosphere, as well as modelled HCFC-22 from a 39-year run of the Canadian Middle Atmosphere Model (CMAM39) in the same region.
Gitaek T. Lee, Rokjin J. Park, Hyeong-Ahn Kwon, Eunjo S. Ha, Sieun D. Lee, Seunga Shin, Myoung-Hwan Ahn, Mina Kang, Yong-Sang Choi, Gyuyeon Kim, Dong-Won Lee, Deok-Rae Kim, Hyunkee Hong, Bavo Langerock, Corinne Vigouroux, Christophe Lerot, Francois Hendrick, Gaia Pinardi, Isabelle De Smedt, Michel Van Roozendael, Pucai Wang, Heesung Chong, Yeseul Cho, and Jhoon Kim
Atmos. Chem. Phys., 24, 4733–4749, https://doi.org/10.5194/acp-24-4733-2024, https://doi.org/10.5194/acp-24-4733-2024, 2024
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This study evaluates the Geostationary Environment Monitoring Spectrometer (GEMS) HCHO product by comparing its vertical column densities (VCDs) with those of TROPOMI and ground-based observations. Based on some sensitivity tests, obtaining radiance references under clear-sky conditions significantly improves HCHO retrieval quality. GEMS HCHO VCDs captured seasonal and diurnal variations well during the first year of observation, showing consistency with TROPOMI and ground-based observations.
Jean-François Müller, Trissevgeni Stavrakou, Glenn-Michael Oomen, Beata Opacka, Isabelle De Smedt, Alex Guenther, Corinne Vigouroux, Bavo Langerock, Carlos Augusto Bauer Aquino, Michel Grutter, James Hannigan, Frank Hase, Rigel Kivi, Erik Lutsch, Emmanuel Mahieu, Maria Makarova, Jean-Marc Metzger, Isamu Morino, Isao Murata, Tomoo Nagahama, Justus Notholt, Ivan Ortega, Mathias Palm, Amelie Röhling, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, and Alan Fried
Atmos. Chem. Phys., 24, 2207–2237, https://doi.org/10.5194/acp-24-2207-2024, https://doi.org/10.5194/acp-24-2207-2024, 2024
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Formaldehyde observations from satellites can be used to constrain the emissions of volatile organic compounds, but those observations have biases. Using an atmospheric model, aircraft and ground-based remote sensing data, we quantify these biases, propose a correction to the data, and assess the consequence of this correction for the evaluation of emissions.
Minqiang Zhou, Bavo Langerock, Mahesh Kumar Sha, Christian Hermans, Nicolas Kumps, Rigel Kivi, Pauli Heikkinen, Christof Petri, Justus Notholt, Huilin Chen, and Martine De Mazière
Atmos. Meas. Tech., 16, 5593–5608, https://doi.org/10.5194/amt-16-5593-2023, https://doi.org/10.5194/amt-16-5593-2023, 2023
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Atmospheric N2O and CH4 columns are successfully retrieved from low-resolution FTIR spectra recorded by a Bruker VERTEX 70. The 1-year measurements at Sodankylä show that the N2O total columns retrieved from 125HR and VERTEX 70 spectra are −0.3 ± 0.7 % with an R value of 0.93. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX spectra are 0.0 ± 0.8 % with an R value of 0.87. Such a technique can help to fill the gap in NDACC N2O and CH4 measurements.
Sieglinde Callewaert, Minqiang Zhou, Bavo Langerock, Pucai Wang, Ting Wang, Emmanuel Mahieu, and Martine De Mazière
EGUsphere, https://doi.org/10.5194/egusphere-2023-2103, https://doi.org/10.5194/egusphere-2023-2103, 2023
Preprint archived
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We used an atmospheric transport model and satellite data to study greenhouse gas observations at Xianghe, China. Our study shows the key source sectors that influence the concentrations and their respective importance. Furthermore, meteorological factors such as wind direction are discussed. This research highlights the challenges in accurately simulating these kind of measurements and helps us to better understand greenhouse gas variability in the region.
Yuhang Zhang, Jintai Lin, Jhoon Kim, Hanlim Lee, Junsung Park, Hyunkee Hong, Michel Van Roozendael, Francois Hendrick, Ting Wang, Pucai Wang, Qin He, Kai Qin, Yongjoo Choi, Yugo Kanaya, Jin Xu, Pinhua Xie, Xin Tian, Sanbao Zhang, Shanshan Wang, Siyang Cheng, Xinghong Cheng, Jianzhong Ma, Thomas Wagner, Robert Spurr, Lulu Chen, Hao Kong, and Mengyao Liu
Atmos. Meas. Tech., 16, 4643–4665, https://doi.org/10.5194/amt-16-4643-2023, https://doi.org/10.5194/amt-16-4643-2023, 2023
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Our tropospheric NO2 vertical column density product with high spatiotemporal resolution is based on the Geostationary Environment Monitoring Spectrometer (GEMS) and named POMINO–GEMS. Strong hotspot signals and NO2 diurnal variations are clearly seen. Validations with multiple satellite products and ground-based, mobile car and surface measurements exhibit the overall great performance of the POMINO–GEMS product, indicating its capability for application in environmental studies.
Rafaella Chiarella, Matthias Buschmann, Joshua Laughner, Isamu Morino, Justus Notholt, Christof Petri, Geoffrey Toon, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 16, 3987–4007, https://doi.org/10.5194/amt-16-3987-2023, https://doi.org/10.5194/amt-16-3987-2023, 2023
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The goal is to establish a window and strategy for xCO2 retrieval from ground-based Fourier transform spectrometers for NDACC. In the study we describe the spectroscopy of the region, the locations and instruments used, and the methods of calculating the retrieved xCO2. We performed tests to assess the sensitivity to diverse factors and sources of errors while comparing the retrieval to a well-established xCO2 retrieval from TCCON.
Ruosi Liang, Yuzhong Zhang, Wei Chen, Peixuan Zhang, Jingran Liu, Cuihong Chen, Huiqin Mao, Guofeng Shen, Zhen Qu, Zichong Chen, Minqiang Zhou, Pucai Wang, Robert J. Parker, Hartmut Boesch, Alba Lorente, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 8039–8057, https://doi.org/10.5194/acp-23-8039-2023, https://doi.org/10.5194/acp-23-8039-2023, 2023
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We compare and evaluate East Asian methane emissions inferred from different satellite observations (GOSAT and TROPOMI). The results show discrepancies over northern India and eastern China. Independent ground-based observations are more consistent with TROPOMI-derived emissions in northern India and GOSAT-derived emissions in eastern China.
Harrison A. Parker, Joshua L. Laughner, Geoffrey C. Toon, Debra Wunch, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Kathryn McKain, Bianca C. Baier, and Paul O. Wennberg
Atmos. Meas. Tech., 16, 2601–2625, https://doi.org/10.5194/amt-16-2601-2023, https://doi.org/10.5194/amt-16-2601-2023, 2023
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We describe a retrieval algorithm for determining limited information about the vertical distribution of carbon monoxide (CO) and carbon dioxide (CO2) from total column observations from ground-based observations. Our retrieved partial column values compare well with integrated in situ data. The average error for our retrieval is 1.51 ppb (~ 2 %) for CO and 5.09 ppm (~ 1.25 %) for CO2. We anticipate that this approach will find broad application for use in carbon cycle science.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
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We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Yu Someya, Yukio Yoshida, Hirofumi Ohyama, Shohei Nomura, Akihide Kamei, Isamu Morino, Hitoshi Mukai, Tsuneo Matsunaga, Joshua L. Laughner, Voltaire A. Velazco, Benedikt Herkommer, Yao Té, Mahesh Kumar Sha, Rigel Kivi, Minqiang Zhou, Young Suk Oh, Nicholas M. Deutscher, and David W. T. Griffith
Atmos. Meas. Tech., 16, 1477–1501, https://doi.org/10.5194/amt-16-1477-2023, https://doi.org/10.5194/amt-16-1477-2023, 2023
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The updated retrieval algorithm for the Greenhouse gases Observing SATellite level 2 product is presented. The main changes in the algorithm from the previous one are the treatment of cirrus clouds, the degradation model of the sensor, solar irradiance, and gas absorption coefficient tables. The retrieval results showed improvements in fitting accuracy and an increase in the data amount over land. On the other hand, there are still large biases of XCO2 which should be corrected over the ocean.
Nasrin Mostafavi Pak, Jacob K. Hedelius, Sébastien Roche, Liz Cunningham, Bianca Baier, Colm Sweeney, Coleen Roehl, Joshua Laughner, Geoffrey Toon, Paul Wennberg, Harrison Parker, Colin Arrowsmith, Joseph Mendonca, Pierre Fogal, Tyler Wizenberg, Beatriz Herrera, Kimberly Strong, Kaley A. Walker, Felix Vogel, and Debra Wunch
Atmos. Meas. Tech., 16, 1239–1261, https://doi.org/10.5194/amt-16-1239-2023, https://doi.org/10.5194/amt-16-1239-2023, 2023
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Ground-based remote sensing instruments in the Total Carbon Column Observing Network (TCCON) measure greenhouse gases in the atmosphere. Consistency between TCCON measurements is crucial to accurately infer changes in atmospheric composition. We use portable remote sensing instruments (EM27/SUN) to evaluate biases between TCCON stations in North America. We also improve the retrievals of EM27/SUN instruments and evaluate the previous (GGG2014) and newest (GGG2020) retrieval algorithms.
Joshua L. Laughner, Sébastien Roche, Matthäus Kiel, Geoffrey C. Toon, Debra Wunch, Bianca C. Baier, Sébastien Biraud, Huilin Chen, Rigel Kivi, Thomas Laemmel, Kathryn McKain, Pierre-Yves Quéhé, Constantina Rousogenous, Britton B. Stephens, Kaley Walker, and Paul O. Wennberg
Atmos. Meas. Tech., 16, 1121–1146, https://doi.org/10.5194/amt-16-1121-2023, https://doi.org/10.5194/amt-16-1121-2023, 2023
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Observations using sunlight to measure surface-to-space total column of greenhouse gases in the atmosphere need an initial guess of the vertical distribution of those gases to start from. We have developed an approach to provide those initial guess profiles that uses readily available meteorological data as input. This lets us make these guesses without simulating them with a global model. The profiles generated this way match independent observations well.
Amir H. Souri, Matthew S. Johnson, Glenn M. Wolfe, James H. Crawford, Alan Fried, Armin Wisthaler, William H. Brune, Donald R. Blake, Andrew J. Weinheimer, Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Corinne Vigouroux, Bavo Langerock, Sungyeon Choi, Lok Lamsal, Lei Zhu, Shuai Sun, Ronald C. Cohen, Kyung-Eun Min, Changmin Cho, Sajeev Philip, Xiong Liu, and Kelly Chance
Atmos. Chem. Phys., 23, 1963–1986, https://doi.org/10.5194/acp-23-1963-2023, https://doi.org/10.5194/acp-23-1963-2023, 2023
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We have rigorously characterized different sources of error in satellite-based HCHO / NO2 tropospheric columns, a widely used metric for diagnosing near-surface ozone sensitivity. Specifically, the errors were categorized/quantified into (i) an inherent chemistry error, (ii) the decoupled relationship between columns and the near-surface concentration, (iii) the spatial representativeness error of ground satellite pixels, and (iv) the satellite retrieval errors.
Minqiang Zhou, Bavo Langerock, Pucai Wang, Corinne Vigouroux, Qichen Ni, Christian Hermans, Bart Dils, Nicolas Kumps, Weidong Nan, and Martine De Mazière
Atmos. Meas. Tech., 16, 273–293, https://doi.org/10.5194/amt-16-273-2023, https://doi.org/10.5194/amt-16-273-2023, 2023
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The ground-based FTIR measurements at Xianghe provide carbon monoxide (CO), acetylene (C2H2), ethane (C2H6), formaldehyde (H2CO), and hydrogen cyanide (HCN) total columns between June 2018 and November 2021. The retrieval strategies, information, and uncertainties of these five important trace gases are presented and discussed. This study provides insight into the time series, variations, and correlations of these five species in northern China.
Xiangyu Zeng, Wei Wang, Cheng Liu, Changgong Shan, Yu Xie, Peng Wu, Qianqian Zhu, Minqiang Zhou, Martine De Mazière, Emmanuel Mahieu, Irene Pardo Cantos, Jamal Makkor, and Alexander Polyakov
Atmos. Meas. Tech., 15, 6739–6754, https://doi.org/10.5194/amt-15-6739-2022, https://doi.org/10.5194/amt-15-6739-2022, 2022
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CFC-11 and CFC-12, which are classified as ozone-depleting substances, also have high global warming potentials. This paper describes obtaining the CFC-11 and CFC-12 total columns from the solar spectra based on ground-based Fourier transform infrared spectroscopy at Hefei, China. The seasonal variation and annual trend of the two gases are analyzed, and then the data are compared with other independent datasets.
Antje Inness, Ilse Aben, Melanie Ades, Tobias Borsdorff, Johannes Flemming, Luke Jones, Jochen Landgraf, Bavo Langerock, Philippe Nedelec, Mark Parrington, and Roberto Ribas
Atmos. Chem. Phys., 22, 14355–14376, https://doi.org/10.5194/acp-22-14355-2022, https://doi.org/10.5194/acp-22-14355-2022, 2022
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The Copernicus Atmosphere Monitoring Service (CAMS) provides daily global air quality forecasts to users worldwide. One of the species of interest is carbon monoxide (CO), an important trace gas in the atmosphere with anthropogenic and natural sources, produced by incomplete combustion, for example, by wildfires. This paper looks at how well CAMS can model CO in the atmosphere and shows that the fields can be improved when blending CO data from the TROPOMI instrument with the CAMS model.
Minqiang Zhou, Bavo Langerock, Pucai Wang, Corinne Vigouroux, Qichen Ni, Christian Hermans, Bart Dils, Nicolas Kumps, Weidong Nan, and Martine De Mazière
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-354, https://doi.org/10.5194/acp-2022-354, 2022
Revised manuscript not accepted
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The ground-based FTIR measurements at Xianghe provide carbon monoxide (CO), acetylene (C2H2), ethane (C2H6), formaldehyde (H2CO), and hydrogen cyanide (HCN) total columns between June 2018 and November 2021. The retrieval strategies, retrieval information, and uncertainties of these five important trace gases are presented and discussed. This study provides an insight into the time series, variations, and correlations of these five species in North China.
Sieglinde Callewaert, Jérôme Brioude, Bavo Langerock, Valentin Duflot, Dominique Fonteyn, Jean-François Müller, Jean-Marc Metzger, Christian Hermans, Nicolas Kumps, Michel Ramonet, Morgan Lopez, Emmanuel Mahieu, and Martine De Mazière
Atmos. Chem. Phys., 22, 7763–7792, https://doi.org/10.5194/acp-22-7763-2022, https://doi.org/10.5194/acp-22-7763-2022, 2022
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A regional atmospheric transport model is used to analyze the factors contributing to CO2, CH4, and CO observations at Réunion Island. We show that the surface observations are dominated by local fluxes and dynamical processes, while the column data are influenced by larger-scale mechanisms such as biomass burning plumes. The model is able to capture the measured time series well; however, the results are highly dependent on accurate boundary conditions and high-resolution emission inventories.
Saheba Bhatnagar, Mahesh Kumar Sha, Laurence Gill, Bavo Langerock, and Bidisha Ghosh
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-88, https://doi.org/10.5194/bg-2022-88, 2022
Revised manuscript not accepted
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Different land types emit a different quantity of methane, with wetlands being one of the largest sources of methane emissions, contributing to climate change. This study finds variations in land types using the methane total column data from Sentinel 5-precursor satellite with a machine learning algorithm. The variations in land types were identified with high confidence, demonstrating that the methane emissions from the wetland and other land types substantially affect the total column.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
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We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
Christophe Lerot, François Hendrick, Michel Van Roozendael, Leonardo M. A. Alvarado, Andreas Richter, Isabelle De Smedt, Nicolas Theys, Jonas Vlietinck, Huan Yu, Jeroen Van Gent, Trissevgeni Stavrakou, Jean-François Müller, Pieter Valks, Diego Loyola, Hitoshi Irie, Vinod Kumar, Thomas Wagner, Stefan F. Schreier, Vinayak Sinha, Ting Wang, Pucai Wang, and Christian Retscher
Atmos. Meas. Tech., 14, 7775–7807, https://doi.org/10.5194/amt-14-7775-2021, https://doi.org/10.5194/amt-14-7775-2021, 2021
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Global measurements of glyoxal tropospheric columns from the satellite instrument TROPOMI are presented. Such measurements can contribute to the estimation of atmospheric emissions of volatile organic compounds. This new glyoxal product has been fully characterized with a comprehensive error budget, with comparison with other satellite data sets as well as with validation based on independent ground-based remote sensing glyoxal observations.
Wenying He, Hongbin Chen, Yuejian Xuan, Jun Li, Minzheng Duan, and Weidong Nan
Atmos. Meas. Tech., 14, 7069–7078, https://doi.org/10.5194/amt-14-7069-2021, https://doi.org/10.5194/amt-14-7069-2021, 2021
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Large microwave surface emissivities (ε) cause difficulties in widely using satellite microwave data over land. Usually, ground-based radiometers are fixed to a scan field to obtain the temporal evolution of ε over a single land-cover area. To obtain the long-term temporal evolution of ε over different land-cover surfaces simultaneously, we developed a ground mobile observation system to enhance in situ ε observations and presented some preliminary results.
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
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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.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
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This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
Minqiang Zhou, Bavo Langerock, Corinne Vigouroux, Bart Dils, Christian Hermans, Nicolas Kumps, Weidong Nan, Jean-Marc Metzger, Emmanuel Mahieu, Ting Wang, Pucai Wang, and Martine De Mazière
Atmos. Meas. Tech., 14, 6233–6247, https://doi.org/10.5194/amt-14-6233-2021, https://doi.org/10.5194/amt-14-6233-2021, 2021
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NO is a key active trace gas in the atmosphere, which affects the atmospheric environment and human health. In this study, we show that the tropospheric and stratospheric NO partial columns can be observed from the ground-based FTIR measurements at a polluted site (Xianghe, China), but only stratospheric NO partial columns can be observed at a background site (Maïdo, Reunion Island). The variations in the NO observed by the FTIR measurements at the two sites are analyzed and discussed.
Masanori Takeda, Hideaki Nakajima, Isao Murata, Tomoo Nagahama, Isamu Morino, Geoffrey C. Toon, Ray F. Weiss, Jens Mühle, Paul B. Krummel, Paul J. Fraser, and Hsiang-Jui Wang
Atmos. Meas. Tech., 14, 5955–5976, https://doi.org/10.5194/amt-14-5955-2021, https://doi.org/10.5194/amt-14-5955-2021, 2021
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This paper presents the first observations of atmospheric HFC-23 abundances with a ground-based remote sensing technique. The increasing trend of the HFC-23 abundances analyzed by this study agrees with that derived from other existing in situ measurements. This study indicates that ground-based FTIR observation has the capability to monitor the trend of atmospheric HFC-23 and could allow for monitoring the distribution of global atmospheric HFC-23 abundances in more detail.
Matthias M. Frey, Frank Hase, Thomas Blumenstock, Darko Dubravica, Jochen Groß, Frank Göttsche, Martin Handjaba, Petrus Amadhila, Roland Mushi, Isamu Morino, Kei Shiomi, Mahesh Kumar Sha, Martine de Mazière, and David F. Pollard
Atmos. Meas. Tech., 14, 5887–5911, https://doi.org/10.5194/amt-14-5887-2021, https://doi.org/10.5194/amt-14-5887-2021, 2021
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In this study, we present measurements of carbon dioxide, methane and carbon monoxide from a recently established site in Gobabeb, Namibia. Gobabeb is the first site observing these gases on the African mainland and improves the global coverage of measurement sites. Gobabeb is a hyperarid desert site, offering unique characteristics. Measurements started 2015 as part of the COllaborative Carbon Column Observing Network. We compare our results with other datasets and find a good agreement.
Isabelle De Smedt, Gaia Pinardi, Corinne Vigouroux, Steven Compernolle, Alkis Bais, Nuria Benavent, Folkert Boersma, Ka-Lok Chan, Sebastian Donner, Kai-Uwe Eichmann, Pascal Hedelt, François Hendrick, Hitoshi Irie, Vinod Kumar, Jean-Christopher Lambert, Bavo Langerock, Christophe Lerot, Cheng Liu, Diego Loyola, Ankie Piters, Andreas Richter, Claudia Rivera Cárdenas, Fabian Romahn, Robert George Ryan, Vinayak Sinha, Nicolas Theys, Jonas Vlietinck, Thomas Wagner, Ting Wang, Huan Yu, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 12561–12593, https://doi.org/10.5194/acp-21-12561-2021, https://doi.org/10.5194/acp-21-12561-2021, 2021
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This paper assess the performances of the TROPOMI formaldehyde observations compared to its predecessor OMI at different spatial and temporal scales. We also use a global network of MAX-DOAS instruments to validate both satellite datasets for a large range of HCHO columns. The precision obtained with daily TROPOMI observations is comparable to monthly OMI observations. We present clear detection of weak HCHO column enhancements related to shipping emissions in the Indian Ocean.
Yang Yang, Minqiang Zhou, Ting Wang, Bo Yao, Pengfei Han, Denghui Ji, Wei Zhou, Yele Sun, Gengchen Wang, and Pucai Wang
Atmos. Chem. Phys., 21, 11741–11757, https://doi.org/10.5194/acp-21-11741-2021, https://doi.org/10.5194/acp-21-11741-2021, 2021
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This study introduces the in situ CO2 measurement system installed in Beijing (urban), Xianghe (suburban), and Xinglong (rural) in North China for the first time. The spatial and temporal variations in CO2 mole fractions at the three sites between June 2018 and April 2020 are discussed on both seasonal and diurnal scales.
Geoffrey C. Toon, Jean-Francois L. Blavier, Keeyoon Sung, and Katelyn Yu
Atmos. Chem. Phys., 21, 10727–10743, https://doi.org/10.5194/acp-21-10727-2021, https://doi.org/10.5194/acp-21-10727-2021, 2021
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We report measurements of atmospheric propane (C3H8) from analysis of ground-based infra-red solar absorption spectra measured from various sites by the Jet Propulsion Laboratory (JPL) MkIV interferometer. These measurements suggest that exploitation of natural gas fields is a major and growing source of propane in the USA. Also, there seem to be propane sources in large cities such as Los Angeles, possibly related to use of liquefied petroleum gas (LPG).
Matthieu Dogniaux, Cyril Crevoisier, Raymond Armante, Virginie Capelle, Thibault Delahaye, Vincent Cassé, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. Garcia, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, David F. Pollard, Coleen M. Roehl, Kei Shiomi, Kimberly Strong, Yao Té, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 14, 4689–4706, https://doi.org/10.5194/amt-14-4689-2021, https://doi.org/10.5194/amt-14-4689-2021, 2021
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We present the Adaptable 4A Inversion (5AI), an implementation of the optimal estimation (OE) algorithm, relying on the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer model, that enables the retrieval of greenhouse gas atmospheric weighted columns from infrared measurements. It is tested on a sample of Orbiting Carbon Observatory-2 observations, and its results satisfactorily compare to several reference products, thus showing the reliability of 5AI OE implementation.
Sébastien Roche, Kimberly Strong, Debra Wunch, Joseph Mendonca, Colm Sweeney, Bianca Baier, Sébastien C. Biraud, Joshua L. Laughner, Geoffrey C. Toon, and Brian J. Connor
Atmos. Meas. Tech., 14, 3087–3118, https://doi.org/10.5194/amt-14-3087-2021, https://doi.org/10.5194/amt-14-3087-2021, 2021
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We evaluate CO2 profile retrievals from ground-based near-infrared solar absorption spectra after implementing several improvements to the GFIT2 retrieval algorithm. Realistic errors in the a priori temperature profile (~ 2 °C in the lower troposphere) are found to be the leading source of differences between the retrieved and true CO2 profiles, differences that are larger than typical CO2 variability. A temperature retrieval or correction is critical to improve CO2 profile retrieval results.
Di Liu, Wanqi Sun, Ning Zeng, Pengfei Han, Bo Yao, Zhiqiang Liu, Pucai Wang, Ke Zheng, Han Mei, and Qixiang Cai
Atmos. Chem. Phys., 21, 4599–4614, https://doi.org/10.5194/acp-21-4599-2021, https://doi.org/10.5194/acp-21-4599-2021, 2021
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It is difficult to directly observe the COVID-19 signals in CO2 due to the strong weather induced variations. Here, we determined the on-road CO2 concentration declines in Beijing using mobile observatory data before (BC), during (DC) and after COVID-19 (AC). We chose trips with the most similar weather and calculated the enhancement, the difference between on-road and the city “background”. We showed a clear on-road CO2 decrease in DC, which is consistent with the emissions reductions in DC.
Sophie Vandenbussche, Sieglinde Callewaert, Kerstin Schepanski, and Martine De Mazière
Atmos. Chem. Phys., 20, 15127–15146, https://doi.org/10.5194/acp-20-15127-2020, https://doi.org/10.5194/acp-20-15127-2020, 2020
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Mineral dust aerosols blown mostly from desert areas are a key player in the climate system. We use a new desert dust aerosol low-altitude concentration data set as well as additional information on the surface state and low-altitude winds to infer desert dust emission and source maps over North Africa. With 9 years of data, we observe a full seasonal cycle of dust emissions, differentiating morning and afternoon/evening emissions and providing a first glance at long-term changes.
Minqiang Zhou, Pucai Wang, Bavo Langerock, Corinne Vigouroux, Christian Hermans, Nicolas Kumps, Ting Wang, Yang Yang, Denghui Ji, Liang Ran, Jinqiang Zhang, Yuejian Xuan, Hongbin Chen, Françoise Posny, Valentin Duflot, Jean-Marc Metzger, and Martine De Mazière
Atmos. Meas. Tech., 13, 5379–5394, https://doi.org/10.5194/amt-13-5379-2020, https://doi.org/10.5194/amt-13-5379-2020, 2020
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We study O3 retrievals in the 3040 cm-1 spectral range from FTIR measurements at Xianghe China (39.75° N, 116.96° E; 50 m a.s.l.) between June 2018 and December 2019. It was found that the FTIR O3 (3040 cm-1) retrievals capture the seasonal and synoptic variations of O3 very well. The systematic and random uncertainties of FTIR O3 (3040 cm-1) total column are about 13.6 % and 1.4 %, respectively. The DOFS is 2.4±0.3 (1σ), with two individual pieces of information in surface–20 km and 20–40 km.
Mahesh Kumar Sha, Martine De Mazière, Justus Notholt, Thomas Blumenstock, Huilin Chen, Angelika Dehn, David W. T. Griffith, Frank Hase, Pauli Heikkinen, Christian Hermans, Alex Hoffmann, Marko Huebner, Nicholas Jones, Rigel Kivi, Bavo Langerock, Christof Petri, Francis Scolas, Qiansi Tu, and Damien Weidmann
Atmos. Meas. Tech., 13, 4791–4839, https://doi.org/10.5194/amt-13-4791-2020, https://doi.org/10.5194/amt-13-4791-2020, 2020
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We present the results of the 2017 FRM4GHG campaign at the Sodankylä TCCON site aimed at characterising the assessment of several low-cost portable instruments for precise solar absorption measurements of column-averaged dry-air mole fractions of CO2, CH4, and CO. The test instruments provided stable and precise measurements of these gases with quantified small biases. This qualifies the instruments to complement TCCON and expand the global coverage of ground-based measurements of these gases.
Thomas von Clarmann, Douglas A. Degenstein, Nathaniel J. Livesey, Stefan Bender, Amy Braverman, André Butz, Steven Compernolle, Robert Damadeo, Seth Dueck, Patrick Eriksson, Bernd Funke, Margaret C. Johnson, Yasuko Kasai, Arno Keppens, Anne Kleinert, Natalya A. Kramarova, Alexandra Laeng, Bavo Langerock, Vivienne H. Payne, Alexei Rozanov, Tomohiro O. Sato, Matthias Schneider, Patrick Sheese, Viktoria Sofieva, Gabriele P. Stiller, Christian von Savigny, and Daniel Zawada
Atmos. Meas. Tech., 13, 4393–4436, https://doi.org/10.5194/amt-13-4393-2020, https://doi.org/10.5194/amt-13-4393-2020, 2020
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Remote sensing of atmospheric state variables typically relies on the inverse solution of the radiative transfer equation. An adequately characterized retrieval provides information on the uncertainties of the estimated state variables as well as on how any constraint or a priori assumption affects the estimate. This paper summarizes related techniques and provides recommendations for unified error reporting.
Yang Yang, Minqiang Zhou, Bavo Langerock, Mahesh Kumar Sha, Christian Hermans, Ting Wang, Denghui Ji, Corinne Vigouroux, Nicolas Kumps, Gengchen Wang, Martine De Mazière, and Pucai Wang
Earth Syst. Sci. Data, 12, 1679–1696, https://doi.org/10.5194/essd-12-1679-2020, https://doi.org/10.5194/essd-12-1679-2020, 2020
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The column-averaged dry-air mole fractions of CO2 (XCO2), CH4 (XCH4) and CO (XCO) have been measured with a Bruker IFS 125HR Fourier-transform infrared spectrometer (FTIR) at Xianghe (39.75° N, 116.96° E, north China) since June 2018. The instrumental setup follows the guidelines of the Total Carbon Column Observing Network (TCCON). The site and the FTIR system are described in this study. The FTIR measurements are discussed and have been applied for satellite validations.
Corinne Vigouroux, Bavo Langerock, Carlos Augusto Bauer Aquino, Thomas Blumenstock, Zhibin Cheng, Martine De Mazière, Isabelle De Smedt, Michel Grutter, James W. Hannigan, Nicholas Jones, Rigel Kivi, Diego Loyola, Erik Lutsch, Emmanuel Mahieu, Maria Makarova, Jean-Marc Metzger, Isamu Morino, Isao Murata, Tomoo Nagahama, Justus Notholt, Ivan Ortega, Mathias Palm, Gaia Pinardi, Amelie Röhling, Dan Smale, Wolfgang Stremme, Kim Strong, Ralf Sussmann, Yao Té, Michel van Roozendael, Pucai Wang, and Holger Winkler
Atmos. Meas. Tech., 13, 3751–3767, https://doi.org/10.5194/amt-13-3751-2020, https://doi.org/10.5194/amt-13-3751-2020, 2020
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We validate the TROPOMI HCHO product with ground-based FTIR (Fourier-transform infrared) measurements from 25 stations. We find that TROPOMI overestimates HCHO under clean conditions, while it underestimates it at high HCHO levels. Both TROPOMI precision and accuracy reach the pre-launch requirements, and its precision can even be 2 times better. The observed TROPOMI seasonal variability is in agreement with the FTIR data. The TROPOMI random uncertainty and data filtering should be refined.
Youwen Sun, Cheng Liu, Lin Zhang, Mathias Palm, Justus Notholt, Hao Yin, Corinne Vigouroux, Erik Lutsch, Wei Wang, Changong Shan, Thomas Blumenstock, Tomoo Nagahama, Isamu Morino, Emmanuel Mahieu, Kimberly Strong, Bavo Langerock, Martine De Mazière, Qihou Hu, Huifang Zhang, Christof Petri, and Jianguo Liu
Atmos. Chem. Phys., 20, 5437–5456, https://doi.org/10.5194/acp-20-5437-2020, https://doi.org/10.5194/acp-20-5437-2020, 2020
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We present multiyear time series of ground-based Fourier-transform infrared spectroscopy measurements of HCN in densely populated eastern China. The seasonality and interannual variability of tropospheric HCN columns were investigated. The potential sources that drive the observed HCN seasonality and interannual variability were determined using a GEOS-Chem tagged CO simulation, global fire maps, and potential source contribution function values calculated using HYSPLIT back trajectories.
Karin Kreher, Michel Van Roozendael, Francois Hendrick, Arnoud Apituley, Ermioni Dimitropoulou, Udo Frieß, Andreas Richter, Thomas Wagner, Johannes Lampel, Nader Abuhassan, Li Ang, Monica Anguas, Alkis Bais, Nuria Benavent, Tim Bösch, Kristof Bognar, Alexander Borovski, Ilya Bruchkouski, Alexander Cede, Ka Lok Chan, Sebastian Donner, Theano Drosoglou, Caroline Fayt, Henning Finkenzeller, David Garcia-Nieto, Clio Gielen, Laura Gómez-Martín, Nan Hao, Bas Henzing, Jay R. Herman, Christian Hermans, Syedul Hoque, Hitoshi Irie, Junli Jin, Paul Johnston, Junaid Khayyam Butt, Fahim Khokhar, Theodore K. Koenig, Jonas Kuhn, Vinod Kumar, Cheng Liu, Jianzhong Ma, Alexis Merlaud, Abhishek K. Mishra, Moritz Müller, Monica Navarro-Comas, Mareike Ostendorf, Andrea Pazmino, Enno Peters, Gaia Pinardi, Manuel Pinharanda, Ankie Piters, Ulrich Platt, Oleg Postylyakov, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Alfonso Saiz-Lopez, Anja Schönhardt, Stefan F. Schreier, André Seyler, Vinayak Sinha, Elena Spinei, Kimberly Strong, Frederik Tack, Xin Tian, Martin Tiefengraber, Jan-Lukas Tirpitz, Jeroen van Gent, Rainer Volkamer, Mihalis Vrekoussis, Shanshan Wang, Zhuoru Wang, Mark Wenig, Folkard Wittrock, Pinhua H. Xie, Jin Xu, Margarita Yela, Chengxin Zhang, and Xiaoyi Zhao
Atmos. Meas. Tech., 13, 2169–2208, https://doi.org/10.5194/amt-13-2169-2020, https://doi.org/10.5194/amt-13-2169-2020, 2020
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In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants during an instrument intercomparison campaign (CINDI-2) at Cabauw, the Netherlands. Here we report on the outcome of this intercomparison exercise. The three major goals were to characterise the differences between the participating instruments, to define a robust methodology for performance assessment, and to contribute to the harmonisation of the measurement settings and retrieval methods.
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.
Minqiang Zhou, Bavo Langerock, Mahesh Kumar Sha, Nicolas Kumps, Christian Hermans, Christof Petri, Thorsten Warneke, Huilin Chen, Jean-Marc Metzger, Rigel Kivi, Pauli Heikkinen, Michel Ramonet, and Martine De Mazière
Atmos. Meas. Tech., 12, 6125–6141, https://doi.org/10.5194/amt-12-6125-2019, https://doi.org/10.5194/amt-12-6125-2019, 2019
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In this study, CH4 vertical profile is retrieved by SFIT4 code from FTIR NIR spectra based on six sites during 2016–2017. The degree of freedom for signal of the SFIT4NIR retrieval is about 2.4, with two distinct species of information in the troposphere and in the stratosphere. By comparison against other measurements, e.g. TCCON standard products, satellite observations and AirCore measurements, the uncertainties of the SFIT4NIR total column and partial columns are estimated and discussed.
Minqiang Zhou, Bavo Langerock, Corinne Vigouroux, Mahesh Kumar Sha, Christian Hermans, Jean-Marc Metzger, Huilin Chen, Michel Ramonet, Rigel Kivi, Pauli Heikkinen, Dan Smale, David F. Pollard, Nicholas Jones, Voltaire A. Velazco, Omaira E. García, Matthias Schneider, Mathias Palm, Thorsten Warneke, and Martine De Mazière
Atmos. Meas. Tech., 12, 5979–5995, https://doi.org/10.5194/amt-12-5979-2019, https://doi.org/10.5194/amt-12-5979-2019, 2019
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The differences between the TCCON and NDACC XCO measurements are investigated and discussed based on six NDACC–TCCON sites (Ny-Ålesund, Bremen, Izaña, Saint-Denis, Wollongong and Lauder) using data over the period 2007–2017. The smoothing errors from both TCCON and NDACC measurements are estimated. In addition, the scaling factor of the TCCON XCO data is reassessed by comparing with the AirCore measurements at Sodankylä and Orléans.
Susan S. Kulawik, Sean Crowell, David Baker, Junjie Liu, Kathryn McKain, Colm Sweeney, Sebastien C. Biraud, Steve Wofsy, Christopher W. O'Dell, Paul O. Wennberg, Debra Wunch, Coleen M. Roehl, Nicholas M. Deutscher, Matthäus Kiel, David W. T. Griffith, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Mazière, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, Dave F. Pollard, Isamu Morino, Osamu Uchino, Frank Hase, Dietrich G. Feist, Sébastien Roche, Kimberly Strong, Rigel Kivi, Laura Iraci, Kei Shiomi, Manvendra K. Dubey, Eliezer Sepulveda, Omaira Elena Garcia Rodriguez, Yao Té, Pascal Jeseck, Pauli Heikkinen, Edward J. Dlugokencky, Michael R. Gunson, Annmarie Eldering, David Crisp, Brendan Fisher, and Gregory B. Osterman
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-257, https://doi.org/10.5194/amt-2019-257, 2019
Publication in AMT not foreseen
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This paper provides a benchmark of OCO-2 v8 and ACOS-GOSAT v7.3 XCO2 and lowermost tropospheric (LMT) errors. The paper focuses on the systematic errors and subtracts out validation, co-location, and random errors, looks at the correlation scale-length (spatially and temporally) of systematic errors, finding that the scale lengths are similar to bias correction scale-lengths. The assimilates of the bias correction term is used to place an error on fluxes estimates.
Jacob K. Hedelius, Tai-Long He, Dylan B. A. Jones, Bianca C. Baier, Rebecca R. Buchholz, Martine De Mazière, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Laura T. Iraci, Pascal Jeseck, Matthäus Kiel, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Sébastien Roche, Coleen M. Roehl, Matthias Schneider, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Colm Sweeney, Yao Té, Osamu Uchino, Voltaire A. Velazco, Wei Wang, Thorsten Warneke, Paul O. Wennberg, Helen M. Worden, and Debra Wunch
Atmos. Meas. Tech., 12, 5547–5572, https://doi.org/10.5194/amt-12-5547-2019, https://doi.org/10.5194/amt-12-5547-2019, 2019
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We seek ways to improve the accuracy of column measurements of carbon monoxide (CO) – an important tracer of pollution – made from the MOPITT satellite instrument. We devise a filtering scheme which reduces the scatter and also eliminates bias among the MOPITT detectors. Compared to ground-based observations, MOPITT measurements are about 6 %–8 % higher. When MOPITT data are implemented in a global assimilation model, they tend to reduce the model mismatch with aircraft measurements.
Maxime Prignon, Simon Chabrillat, Daniele Minganti, Simon O'Doherty, Christian Servais, Gabriele Stiller, Geoffrey C. Toon, Martin K. Vollmer, and Emmanuel Mahieu
Atmos. Chem. Phys., 19, 12309–12324, https://doi.org/10.5194/acp-19-12309-2019, https://doi.org/10.5194/acp-19-12309-2019, 2019
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Hydrochlorofluorocarbons (HCFCs) are the first, but temporary, substitution products for the strong ozone-depleting chlorofluorocarbons (CFCs). In this work, we present and validate an improved method to retrieve the most abundant HCFC in the atmosphere, allowing its evolution to be monitored independently in the troposphere and stratosphere. These kinds of contributions are fundamental for scrutinizing the fulfilment of the Montreal Protocol on Substances that Deplete the Ozone Layer.
Sieglinde Callewaert, Sophie Vandenbussche, Nicolas Kumps, Arve Kylling, Xiaoxia Shang, Mika Komppula, Philippe Goloub, and Martine De Mazière
Atmos. Meas. Tech., 12, 3673–3698, https://doi.org/10.5194/amt-12-3673-2019, https://doi.org/10.5194/amt-12-3673-2019, 2019
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This article presents the updated MAPIR algorithm, which uses infrared satellite data to obtain the global 3-D distribution of mineral aerosols. A description of the method together with its technical improvements is given. Additionally, a 10-year data set was generated and used to evaluate this new algorithm against AERONET, CALIOP, CATS and two ground-based lidar stations. We have shown that the new MAPIR algorithm provides reliable aerosol optical depth and dust layer mean altitude profiles.
Anna Agustí-Panareda, Michail Diamantakis, Sébastien Massart, Frédéric Chevallier, Joaquín Muñoz-Sabater, Jérôme Barré, Roger Curcoll, Richard Engelen, Bavo Langerock, Rachel M. Law, Zoë Loh, Josep Anton Morguí, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Coleen Roehl, Alex T. Vermeulen, Thorsten Warneke, and Debra Wunch
Atmos. Chem. Phys., 19, 7347–7376, https://doi.org/10.5194/acp-19-7347-2019, https://doi.org/10.5194/acp-19-7347-2019, 2019
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This paper demonstrates the benefits of using global models with high horizontal resolution to represent atmospheric CO2 patterns associated with evolving weather. The modelling of CO2 weather is crucial to interpret the variability from ground-based and satellite CO2 observations, which can then be used to infer CO2 fluxes in atmospheric inversions. The benefits of high resolution come from an improved representation of the topography, winds, tracer transport and CO2 flux distribution.
Debra Wunch, Dylan B. A. Jones, Geoffrey C. Toon, Nicholas M. Deutscher, Frank Hase, Justus Notholt, Ralf Sussmann, Thorsten Warneke, Jeroen Kuenen, Hugo Denier van der Gon, Jenny A. Fisher, and Joannes D. Maasakkers
Atmos. Chem. Phys., 19, 3963–3980, https://doi.org/10.5194/acp-19-3963-2019, https://doi.org/10.5194/acp-19-3963-2019, 2019
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We used five atmospheric observatories in Europe measuring total column dry-air mole fractions of methane and carbon monoxide to infer methane emissions in the area between the observatories. We find that the methane emissions are overestimated by the state-of-the-art inventories, and that this is likely due, at least in part, to the inventory disaggregation. We find that there is significant uncertainty in the carbon monoxide inventories that requires further investigation.
Minqiang Zhou, Bavo Langerock, Kelley C. Wells, Dylan B. Millet, Corinne Vigouroux, Mahesh Kumar Sha, Christian Hermans, Jean-Marc Metzger, Rigel Kivi, Pauli Heikkinen, Dan Smale, David F. Pollard, Nicholas Jones, Nicholas M. Deutscher, Thomas Blumenstock, Matthias Schneider, Mathias Palm, Justus Notholt, James W. Hannigan, and Martine De Mazière
Atmos. Meas. Tech., 12, 1393–1408, https://doi.org/10.5194/amt-12-1393-2019, https://doi.org/10.5194/amt-12-1393-2019, 2019
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N2O is an important atmospheric gas which is observed by two ground-based FTIR networks (TCCON and NDACC). The difference between NDACC and TCCON XN2O measurements is discussed. It is found that the bias between the two networks is within their combined uncertainties. However, TCCON measurements are affected by a priori profiles. In addition, the TCCON and NDACC N2O measurements are compared with the GEOS-Chem model simulations.
Joseph Mendonca, Kimberly Strong, Debra Wunch, Geoffrey C. Toon, David A. Long, Joseph T. Hodges, Vincent T. Sironneau, and Jonathan E. Franklin
Atmos. Meas. Tech., 12, 35–50, https://doi.org/10.5194/amt-12-35-2019, https://doi.org/10.5194/amt-12-35-2019, 2019
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In order to study the carbon cycle, accurate remote sensing measurements of XCO2 are required. This means that accurate absorption coefficients of CO2 and O2 in the retrieval algorithm are required. We use high-resolution laboratory spectra of O2 to derive accurate absorption coefficients. By applying the O2 absorption coefficients to the retrieval of XCO2 from ground-based solar absorption spectra we show that the error on retrieved XCO2 is decreased.
Mengyao Liu, Jintai Lin, K. Folkert Boersma, Gaia Pinardi, Yang Wang, Julien Chimot, Thomas Wagner, Pinhua Xie, Henk Eskes, Michel Van Roozendael, François Hendrick, Pucai Wang, Ting Wang, Yingying Yan, Lulu Chen, and Ruijing Ni
Atmos. Meas. Tech., 12, 1–21, https://doi.org/10.5194/amt-12-1-2019, https://doi.org/10.5194/amt-12-1-2019, 2019
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China has become the world’s largest emitter of NOx, which mainly comes from vehicle exhaust, power plants, etc. However, there are no official ground-based measurements before 2013, so satellites have been widely used to monitor and analyze NOx pollution here. Aerosol is the key factor influencing the accuracy of the satellite NOx product. Our study provides a more accurate way to account for aerosol's influence compared to current widely used products.
Ting Wang, Pucai Wang, Nicolas Theys, Dan Tong, François Hendrick, Qiang Zhang, and Michel Van Roozendael
Atmos. Chem. Phys., 18, 18063–18078, https://doi.org/10.5194/acp-18-18063-2018, https://doi.org/10.5194/acp-18-18063-2018, 2018
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In the last decade, four temporal regimes of SO2 in China have been identified. After an initial rise, SO2 undergoes two sharp drops in 2007–2008 and 2014–2016, during which 5-year rebounding is sustained. Different mechanisms are tied to North and South China. The industrial emission is responsible for SO2 variation in North China, while in South China the meteorological conditions make a large contribution. The result is crucial to the understanding of SO2 changes and future polices.
Yingjie Zhang, Wei Du, Yuying Wang, Qingqing Wang, Haofei Wang, Haitao Zheng, Fang Zhang, Hongrong Shi, Yuxuan Bian, Yongxiang Han, Pingqing Fu, Francesco Canonaco, André S. H. Prévôt, Tong Zhu, Pucai Wang, Zhanqing Li, and Yele Sun
Atmos. Chem. Phys., 18, 14637–14651, https://doi.org/10.5194/acp-18-14637-2018, https://doi.org/10.5194/acp-18-14637-2018, 2018
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We have a comprehensive characterization of aerosol chemistry and particle growth events at a downwind site of a highly polluted city in the North China Plain. Aerosol particles at the urban downwind site were highly aged and mainly from secondary formation. New particle growth events were also frequently observed on both clean and polluted days. While both sulfate and SOA played important roles in particle growth during clean periods, SOA was more important than sulfate during polluted events.
Youwen Sun, Cheng Liu, Mathias Palm, Corinne Vigouroux, Justus Notholt, Qihou Hu, Nicholas Jones, Wei Wang, Wenjing Su, Wenqiang Zhang, Changong Shan, Yuan Tian, Xingwei Xu, Martine De Mazière, Minqiang Zhou, and Jianguo Liu
Atmos. Chem. Phys., 18, 14569–14583, https://doi.org/10.5194/acp-18-14569-2018, https://doi.org/10.5194/acp-18-14569-2018, 2018
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The seasonal evolution of O3 and its photochemical production regime in a polluted region of eastern China between 2014 and 2017 was investigated using FTS observations. We observed a broad summer O3 maximum in Hefei, China, and the ozone production is mainly NOx limited in spring and summer and is mainly VOC or mixed VOC–NOx limited in autumn and winter.
Tobias Borsdorff, Joost aan de Brugh, Haili Hu, Otto Hasekamp, Ralf Sussmann, Markus Rettinger, Frank Hase, Jochen Gross, Matthias Schneider, Omaira Garcia, Wolfgang Stremme, Michel Grutter, Dietrich G. Feist, Sabrina G. Arnold, Martine De Mazière, Mahesh Kumar Sha, David F. Pollard, Matthäus Kiel, Coleen Roehl, Paul O. Wennberg, Geoffrey C. Toon, and Jochen Landgraf
Atmos. Meas. Tech., 11, 5507–5518, https://doi.org/10.5194/amt-11-5507-2018, https://doi.org/10.5194/amt-11-5507-2018, 2018
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On 13 October 2017, the S5-P satellite was launched with TROPOMI as its only payload. One of the primary products is atmospheric CO observed with daily global coverage and spatial resolution of 7 × 7 km2. The new dataset allows the sensing of CO enhancements above cities and industrial areas and can track pollution transport from biomass burning regions. Through validation with ground-based TCCON measurements we show that the CO data product is already well within the mission requirement.
Minqiang Zhou, Bavo Langerock, Corinne Vigouroux, Mahesh Kumar Sha, Michel Ramonet, Marc Delmotte, Emmanuel Mahieu, Whitney Bader, Christian Hermans, Nicolas Kumps, Jean-Marc Metzger, Valentin Duflot, Zhiting Wang, Mathias Palm, and Martine De Mazière
Atmos. Chem. Phys., 18, 13881–13901, https://doi.org/10.5194/acp-18-13881-2018, https://doi.org/10.5194/acp-18-13881-2018, 2018
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This study focuses on atmospheric CO and CH4 time series and seasonal variations on Reunion Island based on in situ and FTIR measurements from two sites, Saint Denis and Maido. Ground-based in situ and FTIR (NDACC and TCCON) measurements are used to show their complementarity with regards to obtaining the CO and CH4 concentrations at the surface and in the troposphere and stratosphere. FLEXPART and GEOS-Chem models are applied to understand the seasonal variations of CO and CH4 at this site.
Corinne Vigouroux, Carlos Augusto Bauer Aquino, Maite Bauwens, Cornelis Becker, Thomas Blumenstock, Martine De Mazière, Omaira García, Michel Grutter, César Guarin, James Hannigan, Frank Hase, Nicholas Jones, Rigel Kivi, Dmitry Koshelev, Bavo Langerock, Erik Lutsch, Maria Makarova, Jean-Marc Metzger, Jean-François Müller, Justus Notholt, Ivan Ortega, Mathias Palm, Clare Paton-Walsh, Anatoly Poberovskii, Markus Rettinger, John Robinson, Dan Smale, Trissevgeni Stavrakou, Wolfgang Stremme, Kim Strong, Ralf Sussmann, Yao Té, and Geoffrey Toon
Atmos. Meas. Tech., 11, 5049–5073, https://doi.org/10.5194/amt-11-5049-2018, https://doi.org/10.5194/amt-11-5049-2018, 2018
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A few ground-based stations have provided time series of HCHO columns until now, which was not optimal for providing good diagnostics for satellite or model validation. In this work, HCHO time series have been determined in a harmonized way at 21 stations ensuring, in addition to a better spatial and level of abundances coverage, that internal biases within the network have been minimized. This data set shows consistent good agreement with model data and is ready for future satellite validation.
Lianghai Wu, Otto Hasekamp, Haili Hu, Jochen Landgraf, Andre Butz, Joost aan de Brugh, Ilse Aben, Dave F. Pollard, David W. T. Griffith, Dietrich G. Feist, Dmitry Koshelev, Frank Hase, Geoffrey C. Toon, Hirofumi Ohyama, Isamu Morino, Justus Notholt, Kei Shiomi, Laura Iraci, Matthias Schneider, Martine de Mazière, Ralf Sussmann, Rigel Kivi, Thorsten Warneke, Tae-Young Goo, and Yao Té
Atmos. Meas. Tech., 11, 3111–3130, https://doi.org/10.5194/amt-11-3111-2018, https://doi.org/10.5194/amt-11-3111-2018, 2018
Geoffrey C. Toon, Jean-Francois L. Blavier, and Keeyoon Sung
Atmos. Chem. Phys., 18, 5075–5088, https://doi.org/10.5194/acp-18-5075-2018, https://doi.org/10.5194/acp-18-5075-2018, 2018
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Remote sensing measurements of ethene have been made from the ground and from balloons. Ethene can be measured at low altitudes in polluted regions, such as the Los Angeles basin. Here ethene amounts have decreased by a factor of 3 over the past 25 years due to increasingly strict emission control regulations (e.g., on vehicle exhaust).
Martine De Mazière, Anne M. Thompson, Michael J. Kurylo, Jeannette D. Wild, Germar Bernhard, Thomas Blumenstock, Geir O. Braathen, James W. Hannigan, Jean-Christopher Lambert, Thierry Leblanc, Thomas J. McGee, Gerald Nedoluha, Irina Petropavlovskikh, Gunther Seckmeyer, Paul C. Simon, Wolfgang Steinbrecht, and Susan E. Strahan
Atmos. Chem. Phys., 18, 4935–4964, https://doi.org/10.5194/acp-18-4935-2018, https://doi.org/10.5194/acp-18-4935-2018, 2018
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This paper serves as an introduction to the special issue "Twenty-five years of operations of the Network for the Detection of Atmospheric Composition Change (NDACC)". It describes the origins of the network, its actual status, and some perspectives for its future evolution in the context of atmospheric sciences.
Geoffrey C. Toon, Jean-Francois L. Blavier, and Keeyoon Sung
Atmos. Chem. Phys., 18, 1923–1944, https://doi.org/10.5194/acp-18-1923-2018, https://doi.org/10.5194/acp-18-1923-2018, 2018
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OCS is the main form of atmospheric sulfur. It is produced near the earth's surface and destroyed primarily in the stratosphere, where it is converted to stratospheric sulfate aerosol (SSA). SSA plays an important role in atmospheric chemistry and transport and so it is important to better understand the factors that regulate OCS and hence SSA. Ground-based and balloon-borne infrared spectra observed over the past 30 years are analyzed to provide an improved OCS dataset.
Minqiang Zhou, Bavo Langerock, Corinne Vigouroux, Pucai Wang, Christian Hermans, Gabriele Stiller, Kaley A. Walker, Geoff Dutton, Emmanuel Mahieu, and Martine De Mazière
Atmos. Meas. Tech., 11, 651–662, https://doi.org/10.5194/amt-11-651-2018, https://doi.org/10.5194/amt-11-651-2018, 2018
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SF6 total columns are successfully retrieved from FTIR measurements (Saint Denis and Maïdo) at Reunion Island (21° S, 55° E) between 2004 and 2016 using the SFIT4 algorithm: the retrieval strategy and the error budget are discussed. The trend of SF6 is analysed based on the FTIR retrievals at Reunion Island, the in situ measurements at America Samoa (SMO) and the collocated satellite measurements (MIPAS and ACE-FTS) in the southern tropics. The results show good agreement.
Evelyn De Wachter, Nicolas Kumps, Ann Carine Vandaele, Bavo Langerock, and Martine De Mazière
Atmos. Meas. Tech., 10, 4623–4638, https://doi.org/10.5194/amt-10-4623-2017, https://doi.org/10.5194/amt-10-4623-2017, 2017
Peter W. Thorne, Fabio Madonna, Joerg Schulz, Tim Oakley, Bruce Ingleby, Marco Rosoldi, Emanuele Tramutola, Antti Arola, Matthias Buschmann, Anna C. Mikalsen, Richard Davy, Corinne Voces, Karin Kreher, Martine De Maziere, and Gelsomina Pappalardo
Geosci. Instrum. Method. Data Syst., 6, 453–472, https://doi.org/10.5194/gi-6-453-2017, https://doi.org/10.5194/gi-6-453-2017, 2017
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The term system-of-systems with respect to observational capabilities is frequently used, but what does it mean and how can it be assessed? Here, we define one possible interpretation of a system-of-systems architecture that is based upon demonstrable aspects of observing capabilities. We develop a set of assessment strands and then apply these to a set of atmospheric observational networks to decide which observations may be suitable for characterising satellite platforms in future work.
Sophie Vandenbussche and Martine De Mazière
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-809, https://doi.org/10.5194/acp-2017-809, 2017
Revised manuscript not accepted
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This manuscript proposes a new multidisciplinary approach for analysing desert dust aerosols sources. Those aerosols are natural particles uplifted by winds. Part of their emissions is linked to human activities, and they impact significantly our climate. Our method is applied to North-Africa over the years 2008 to 2016, highlighting both the well-known sources and additional small source areas. We also provide the first large-scale (in time and space) analysis of Sahel dust sources.
Kevin S. Olsen, Kimberly Strong, Kaley A. Walker, Chris D. Boone, Piera Raspollini, Johannes Plieninger, Whitney Bader, Stephanie Conway, Michel Grutter, James W. Hannigan, Frank Hase, Nicholas Jones, Martine de Mazière, Justus Notholt, Matthias Schneider, Dan Smale, Ralf Sussmann, and Naoko Saitoh
Atmos. Meas. Tech., 10, 3697–3718, https://doi.org/10.5194/amt-10-3697-2017, https://doi.org/10.5194/amt-10-3697-2017, 2017
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The primary instrument on the Greenhouse gases Observing SATellite (GOSAT) is the Thermal And Near infrared Sensor for carbon Observations (TANSO) Fourier transform spectrometer (FTS). TANSO-FTS has a thermal infrared channel to retrieve vertical profiles of CO2 and CH4 volume mixing ratios in the troposphere. We compare the retrieved vertical profiles of CH4 from TANSO-FTS with those from two other spaceborne FTSs and with ground-based FTS observatories to assess their quality.
Valentin Duflot, Jean-Luc Baray, Guillaume Payen, Nicolas Marquestaut, Francoise Posny, Jean-Marc Metzger, Bavo Langerock, Corinne Vigouroux, Juliette Hadji-Lazaro, Thierry Portafaix, Martine De Mazière, Pierre-Francois Coheur, Cathy Clerbaux, and Jean-Pierre Cammas
Atmos. Meas. Tech., 10, 3359–3373, https://doi.org/10.5194/amt-10-3359-2017, https://doi.org/10.5194/amt-10-3359-2017, 2017
Enrico Dammers, Mark W. Shephard, Mathias Palm, Karen Cady-Pereira, Shannon Capps, Erik Lutsch, Kim Strong, James W. Hannigan, Ivan Ortega, Geoffrey C. Toon, Wolfgang Stremme, Michel Grutter, Nicholas Jones, Dan Smale, Jacob Siemons, Kevin Hrpcek, Denis Tremblay, Martijn Schaap, Justus Notholt, and Jan Willem Erisman
Atmos. Meas. Tech., 10, 2645–2667, https://doi.org/10.5194/amt-10-2645-2017, https://doi.org/10.5194/amt-10-2645-2017, 2017
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Presented here is the validation of the CrIS fast physical retrieval (CFPR) NH3 column and profile measurements using ground-based Fourier transform infrared (FTIR) observations. The overall FTIR and CrIS total columns have a positive correlation of r = 0.77 (N = 218) with very little bias (a slope of 1.02). Furthermore, we find that CrIS and FTIR profile comparison differences are mostly within the range of the estimated retrieval uncertainties, with differences in the range of ~ 20 to 40 %.
Debra Wunch, Paul O. Wennberg, Gregory Osterman, Brendan Fisher, Bret Naylor, Coleen M. Roehl, Christopher O'Dell, Lukas Mandrake, Camille Viatte, Matthäus Kiel, David W. T. Griffith, Nicholas M. Deutscher, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Maziere, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, David Pollard, John Robinson, Isamu Morino, Osamu Uchino, Frank Hase, Thomas Blumenstock, Dietrich G. Feist, Sabrina G. Arnold, Kimberly Strong, Joseph Mendonca, Rigel Kivi, Pauli Heikkinen, Laura Iraci, James Podolske, Patrick W. Hillyard, Shuji Kawakami, Manvendra K. Dubey, Harrison A. Parker, Eliezer Sepulveda, Omaira E. García, Yao Te, Pascal Jeseck, Michael R. Gunson, David Crisp, and Annmarie Eldering
Atmos. Meas. Tech., 10, 2209–2238, https://doi.org/10.5194/amt-10-2209-2017, https://doi.org/10.5194/amt-10-2209-2017, 2017
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This paper describes the comparisons between NASA's Orbiting Carbon Observatory (OCO-2) column-averaged dry-air mole fractions of CO2 with its primary ground-based validation network, the Total Carbon Column Observing Network (TCCON). The paper shows that while the standard bias correction reduces much of the spurious variability in the satellite measurements, residual biases remain.
Rebecca R. Buchholz, Merritt N. Deeter, Helen M. Worden, John Gille, David P. Edwards, James W. Hannigan, Nicholas B. Jones, Clare Paton-Walsh, David W. T. Griffith, Dan Smale, John Robinson, Kimberly Strong, Stephanie Conway, Ralf Sussmann, Frank Hase, Thomas Blumenstock, Emmanuel Mahieu, and Bavo Langerock
Atmos. Meas. Tech., 10, 1927–1956, https://doi.org/10.5194/amt-10-1927-2017, https://doi.org/10.5194/amt-10-1927-2017, 2017
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The study presents the first systematic use of ground-based remote-sensing data from the Network for the Detection of Atmospheric Composition Change (NDACC) to validate satellite-based Measurements of Pollution in the Troposphere (MOPITT) total column carbon monoxide (CO). MOPITT generally shows low bias with respect to the ground-based instruments. The geographic and temporal dependence of validation results are determined. Our findings inform some recommendations for using MOPITT measurements.
Jacob K. Hedelius, Harrison Parker, Debra Wunch, Coleen M. Roehl, Camille Viatte, Sally Newman, Geoffrey C. Toon, James R. Podolske, Patrick W. Hillyard, Laura T. Iraci, Manvendra K. Dubey, and Paul O. Wennberg
Atmos. Meas. Tech., 10, 1481–1493, https://doi.org/10.5194/amt-10-1481-2017, https://doi.org/10.5194/amt-10-1481-2017, 2017
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Two portable spectrometers, assumed to be internally precise, were taken to four different sites with (stationary) TCCON spectrometers. Biases of column averaged CO2 and CH4 measured among the TCCON sites were estimated experimentally. Results suggest that maximum (95 % confidence interval) bias among sites is less than what was estimated from a previous analytical error analysis.
Clio Gielen, François Hendrick, Gaia Pinardi, Isabelle De Smedt, Caroline Fayt, Christian Hermans, Trissevgeni Stavrakou, Maite Bauwens, Jean-Francois Müller, Eugène Ndenzako, Pierre Nzohabonayo, Rachel Akimana, Sebastien Niyonzima, Michel Van Roozendael, and Martine De Mazière
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-1104, https://doi.org/10.5194/acp-2016-1104, 2017
Revised manuscript has not been submitted
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In this paper we study the composition of the lower atmosphere above the Central-African capital city of Burundi (Bujumbura) by measuring the amount of aerosol dust particles and trace gases in the air.
We find that the aerosol and trace gas seasonal and daily variation is driven by the alternation of rain periods and dry periods associated with intense biomass burning in the vicinity of Bujumbura, and the influence of human activities in the city center.
Minqiang Zhou, Corinne Vigouroux, Bavo Langerock, Pucai Wang, Geoff Dutton, Christian Hermans, Nicolas Kumps, Jean-Marc Metzger, Geoff Toon, and Martine De Mazière
Atmos. Meas. Tech., 9, 5621–5636, https://doi.org/10.5194/amt-9-5621-2016, https://doi.org/10.5194/amt-9-5621-2016, 2016
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Profiles of CFC-11, CFC-12 and HCFC-22 have been obtained from FTIR measurements above the Saint-Denis and Maïdo sites at Reunion Island (21° S, 55° E) with low vertical resolution. The trends derived from the FTIR measurements are −0.86 ± 0.12 % and 2.84 ± 0.06 % for CFC-11 and HCFC-22, respectively, for the period 2004 to 2016, and −0.76 ± 0.05 % for CFC-12 for 2009 to 2016, which are consistent with ground-based in situ observations. Our FTIR data and the collocated MIPAS data are in good agreement.
Debra Wunch, Geoffrey C. Toon, Jacob K. Hedelius, Nicholas Vizenor, Coleen M. Roehl, Katherine M. Saad, Jean-François L. Blavier, Donald R. Blake, and Paul O. Wennberg
Atmos. Chem. Phys., 16, 14091–14105, https://doi.org/10.5194/acp-16-14091-2016, https://doi.org/10.5194/acp-16-14091-2016, 2016
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This paper investigates the cause of the known underestimate of bottom-up inventories of methane in California's South Coast Air Basin (SoCAB). We use total column measurements of methane, ethane, carbon monoxide, and other trace gases beginning in the late 1980s to calculate emissions and attribute sources of excess methane to the atmosphere. We conclude that more than half of the excess methane to the SoCAB atmosphere is attributable to processed natural gas.
Katherine M. Saad, Debra Wunch, Nicholas M. Deutscher, David W. T. Griffith, Frank Hase, Martine De Mazière, Justus Notholt, David F. Pollard, Coleen M. Roehl, Matthias Schneider, Ralf Sussmann, Thorsten Warneke, and Paul O. Wennberg
Atmos. Chem. Phys., 16, 14003–14024, https://doi.org/10.5194/acp-16-14003-2016, https://doi.org/10.5194/acp-16-14003-2016, 2016
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Current approaches to constrain the global methane budget assimilate total column measurements into models, but model biases can impact results. We use tropospheric methane columns to evaluate model transport errors and identify a seasonal time lag in the Northern Hemisphere troposphere masked by stratospheric compensating effects. We find systematic biases in the stratosphere will alias into model-derived emissions estimates, especially those in the high Northern latitudes that vary seasonally.
Gaétane Ronsmans, Bavo Langerock, Catherine Wespes, James W. Hannigan, Frank Hase, Tobias Kerzenmacher, Emmanuel Mahieu, Matthias Schneider, Dan Smale, Daniel Hurtmans, Martine De Mazière, Cathy Clerbaux, and Pierre-François Coheur
Atmos. Meas. Tech., 9, 4783–4801, https://doi.org/10.5194/amt-9-4783-2016, https://doi.org/10.5194/amt-9-4783-2016, 2016
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HNO3 concentrations are obtained from the IASI instrument and the data set is characterized for the first time in terms of vertical profiles, averaging kernels and error profiles. A validation is also conducted through a comparison with ground-based FTIR measurements, with good results. The data set is then used to analyse HNO3 spatial and temporal variability for the year 2011. The latitudinal gradient and the large seasonal variability in polar regions are well represented with IASI data.
Liang Ran, Zhaoze Deng, Xiaobin Xu, Peng Yan, Weili Lin, Ying Wang, Ping Tian, Pucai Wang, Weilin Pan, and Daren Lu
Atmos. Chem. Phys., 16, 10441–10454, https://doi.org/10.5194/acp-16-10441-2016, https://doi.org/10.5194/acp-16-10441-2016, 2016
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Vertical profiles of black carbon within 1 km above the ground were measured using a micro-aethalometer attached to a tethered balloon during the VOGA field campaign in summer 2014 at a semirural site in the North China Plain. The diurnal cycle of black carbon vertical distributions following the development of the mixing layer was analyzed for a selected dataset of 67 profiles.
Enrico Dammers, Mathias Palm, Martin Van Damme, Corinne Vigouroux, Dan Smale, Stephanie Conway, Geoffrey C. Toon, Nicholas Jones, Eric Nussbaumer, Thorsten Warneke, Christof Petri, Lieven Clarisse, Cathy Clerbaux, Christian Hermans, Erik Lutsch, Kim Strong, James W. Hannigan, Hideaki Nakajima, Isamu Morino, Beatriz Herrera, Wolfgang Stremme, Michel Grutter, Martijn Schaap, Roy J. Wichink Kruit, Justus Notholt, Pierre-F. Coheur, and Jan Willem Erisman
Atmos. Chem. Phys., 16, 10351–10368, https://doi.org/10.5194/acp-16-10351-2016, https://doi.org/10.5194/acp-16-10351-2016, 2016
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Atmospheric ammonia (NH3) measured by the IASI satellite instrument is compared to observations from ground-based FTIR instruments. The seasonal cycles of NH3 in both datasets are consistent for most sites. Correlations are found to be high at sites with considerable NH3 levels, whereas correlations are lower at sites with low NH3 levels close to the detection limit of the IASI instrument. The study's results further indicate that the IASI-NH3 product performs better than earlier estimates.
Jacob K. Hedelius, Camille Viatte, Debra Wunch, Coleen M. Roehl, Geoffrey C. Toon, Jia Chen, Taylor Jones, Steven C. Wofsy, Jonathan E. Franklin, Harrison Parker, Manvendra K. Dubey, and Paul O. Wennberg
Atmos. Meas. Tech., 9, 3527–3546, https://doi.org/10.5194/amt-9-3527-2016, https://doi.org/10.5194/amt-9-3527-2016, 2016
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Portable FTS instruments with lower resolution are being used to measure gases (including CO2, CH4, CO, and N2O) in the atmosphere. We compared measurements from four of these instruments for a few weeks, and with one for nearly a year to a higher resolution TCCON standard. We also performed tests to assess performance under different atmospheric and instrumental conditions. We noted consistent offsets in the short-term (~1 month); more research is still needed to assess precision longer term.
Brian J. Connor, Vanessa Sherlock, Geoff Toon, Debra Wunch, and Paul O. Wennberg
Atmos. Meas. Tech., 9, 3513–3525, https://doi.org/10.5194/amt-9-3513-2016, https://doi.org/10.5194/amt-9-3513-2016, 2016
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An algorithm for retrieval of vertical profiles of CO2 from ground-based spectra is described. Retrieval of CO2 vertical profiles from would be very beneficial for carbon cycle studies and the validation of satellite measurements. There are approximately 3 degrees of freedom for the CO2 profile. The accuracy of retrievals of CO2 from the spectral band used is limited by small errors in the calculated spectrum. Ongoing research is needed and described.
Makoto Inoue, Isamu Morino, Osamu Uchino, Takahiro Nakatsuru, Yukio Yoshida, Tatsuya Yokota, Debra Wunch, Paul O. Wennberg, Coleen M. Roehl, David W. T. Griffith, Voltaire A. Velazco, Nicholas M. Deutscher, Thorsten Warneke, Justus Notholt, John Robinson, Vanessa Sherlock, Frank Hase, Thomas Blumenstock, Markus Rettinger, Ralf Sussmann, Esko Kyrö, Rigel Kivi, Kei Shiomi, Shuji Kawakami, Martine De Mazière, Sabrina G. Arnold, Dietrich G. Feist, Erica A. Barrow, James Barney, Manvendra Dubey, Matthias Schneider, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Toshinobu Machida, Yousuke Sawa, Kazuhiro Tsuboi, Hidekazu Matsueda, Colm Sweeney, Pieter P. Tans, Arlyn E. Andrews, Sebastien C. Biraud, Yukio Fukuyama, Jasna V. Pittman, Eric A. Kort, and Tomoaki Tanaka
Atmos. Meas. Tech., 9, 3491–3512, https://doi.org/10.5194/amt-9-3491-2016, https://doi.org/10.5194/amt-9-3491-2016, 2016
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In this study, we correct the biases of GOSAT XCO2 and XCH4 using TCCON data. To evaluate the effectiveness of our correction method, uncorrected/corrected GOSAT data are compared to independent XCO2 and XCH4 data derived from aircraft measurements. Consequently, we suggest that this method is effective for reducing the biases of the GOSAT data. We consider that our work provides GOSAT data users with valuable information and contributes to the further development of studies on greenhouse gases.
Minqiang Zhou, Bart Dils, Pucai Wang, Rob Detmers, Yukio Yoshida, Christopher W. O'Dell, Dietrich G. Feist, Voltaire Almario Velazco, Matthias Schneider, and Martine De Mazière
Atmos. Meas. Tech., 9, 1415–1430, https://doi.org/10.5194/amt-9-1415-2016, https://doi.org/10.5194/amt-9-1415-2016, 2016
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The sun-glint XCO2 and XCH4 products (“ocean data”) of thermal and near infrared sensor for carbon observations Fourier transform spectrometer (TANSO-FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) from several retrieval algorithms is compared with the FTIR measurements form near-ocean Total Carbon Column Observing Network (TCCON) sites, and the results indicate that the ocean data show a good agreement with TCCON measurements.
M. Chirkov, G. P. Stiller, A. Laeng, S. Kellmann, T. von Clarmann, C. D. Boone, J. W. Elkins, A. Engel, N. Glatthor, U. Grabowski, C. M. Harth, M. Kiefer, F. Kolonjari, P. B. Krummel, A. Linden, C. R. Lunder, B. R. Miller, S. A. Montzka, J. Mühle, S. O'Doherty, J. Orphal, R. G. Prinn, G. Toon, M. K. Vollmer, K. A. Walker, R. F. Weiss, A. Wiegele, and D. Young
Atmos. Chem. Phys., 16, 3345–3368, https://doi.org/10.5194/acp-16-3345-2016, https://doi.org/10.5194/acp-16-3345-2016, 2016
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HCFC-22 global distributions from MIPAS measurements for 2005 to 2012 are presented. Tropospheric trends are in good agreement with ground-based observations. A layer of enhanced HCFC-22 in the upper tropospheric tropics and northern subtropics is identified to come from Asian sources uplifted in the Asian monsoon. Stratospheric distributions provide show seasonal, semi-annual, and QBO-related variations. Hemispheric asymmetries of trends hint towards a change in the stratospheric circulation.
Kevin S. Olsen, Geoffrey C. Toon, Chris D. Boone, and Kimberly Strong
Atmos. Meas. Tech., 9, 1063–1082, https://doi.org/10.5194/amt-9-1063-2016, https://doi.org/10.5194/amt-9-1063-2016, 2016
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A new version of the Atmospheric Chemistry Experiment Fourier transform spectrometer was intended to be sent to Mars to perform a detailed study of the composition of the Martian atmosphere. Of critical importance for such a mission is a method to accurately determine the temperature and pressure of the atmosphere. This paper presents a new algorithm for measuring temperature and pressure from high-resolution infrared spectra of CO2 absorption and applies it to terrestrial spectra.
M. Kiel, D. Wunch, P. O. Wennberg, G. C. Toon, F. Hase, and T. Blumenstock
Atmos. Meas. Tech., 9, 669–682, https://doi.org/10.5194/amt-9-669-2016, https://doi.org/10.5194/amt-9-669-2016, 2016
A. Laeng, J. Plieninger, T. von Clarmann, U. Grabowski, G. Stiller, E. Eckert, N. Glatthor, F. Haenel, S. Kellmann, M. Kiefer, A. Linden, S. Lossow, L. Deaver, A. Engel, M. Hervig, I. Levin, M. McHugh, S. Noël, G. Toon, and K. Walker
Atmos. Meas. Tech., 8, 5251–5261, https://doi.org/10.5194/amt-8-5251-2015, https://doi.org/10.5194/amt-8-5251-2015, 2015
E. Dammers, C. Vigouroux, M. Palm, E. Mahieu, T. Warneke, D. Smale, B. Langerock, B. Franco, M. Van Damme, M. Schaap, J. Notholt, and J. W. Erisman
Atmos. Chem. Phys., 15, 12789–12803, https://doi.org/10.5194/acp-15-12789-2015, https://doi.org/10.5194/acp-15-12789-2015, 2015
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We present a new retrieval method for ammonia (NH3) concentrations and total columns from ground-based Fourier transform infrared (FTIR) observations. Observations from Bremen, Lauder, Réunion and Jungfraujoch are used to show the capabilities of the new retrieval. The developed retrieval provides a new way of obtaining time-resolved measurements and will be useful for understanding the dynamics of ammonia concentrations in the atmosphere and for satellite and model validation.
V. Duflot, C. Wespes, L. Clarisse, D. Hurtmans, Y. Ngadi, N. Jones, C. Paton-Walsh, J. Hadji-Lazaro, C. Vigouroux, M. De Mazière, J.-M. Metzger, E. Mahieu, C. Servais, F. Hase, M. Schneider, C. Clerbaux, and P.-F. Coheur
Atmos. Chem. Phys., 15, 10509–10527, https://doi.org/10.5194/acp-15-10509-2015, https://doi.org/10.5194/acp-15-10509-2015, 2015
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We present global distributions of acetylene (C2H2) and hydrogen cyanide (HCN) total
columns derived from the Infrared Atmospheric Sounding Interferometer (IASI). C2H2 and HCN are ubiquitous atmospheric trace gases with medium tropospheric lifetime, which are frequently used as indicators of combustion sources and as tracers for atmospheric transport and chemistry. We show that there is an overall agreement between ground-based and space measurements, as well as model simulations.
N. R. P. Harris, B. Hassler, F. Tummon, G. E. Bodeker, D. Hubert, I. Petropavlovskikh, W. Steinbrecht, J. Anderson, P. K. Bhartia, C. D. Boone, A. Bourassa, S. M. Davis, D. Degenstein, A. Delcloo, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, N. Jones, M. J. Kurylo, E. Kyrölä, M. Laine, S. T. Leblanc, J.-C. Lambert, B. Liley, E. Mahieu, A. Maycock, M. de Mazière, A. Parrish, R. Querel, K. H. Rosenlof, C. Roth, C. Sioris, J. Staehelin, R. S. Stolarski, R. Stübi, J. Tamminen, C. Vigouroux, K. A. Walker, H. J. Wang, J. Wild, and J. M. Zawodny
Atmos. Chem. Phys., 15, 9965–9982, https://doi.org/10.5194/acp-15-9965-2015, https://doi.org/10.5194/acp-15-9965-2015, 2015
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Trends in the vertical distribution of ozone are reported for new and recently revised data sets. The amount of ozone-depleting compounds in the stratosphere peaked in the second half of the 1990s. We examine the trends before and after that peak to see if any change in trend is discernible. The previously reported decreases are confirmed. Furthermore, the downward trend in upper stratospheric ozone has not continued. The possible significance of any increase is discussed in detail.
A. Ostler, R. Sussmann, P. K. Patra, P. O. Wennberg, N. M. Deutscher, D. W. T. Griffith, T. Blumenstock, F. Hase, R. Kivi, T. Warneke, Z. Wang, M. De Mazière, J. Robinson, and H. Ohyama
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-20395-2015, https://doi.org/10.5194/acpd-15-20395-2015, 2015
Preprint withdrawn
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We find that stratospheric model-transport errors are common for chemical transport models that are used for inverse estimates of CH4 emissions. These model-transport errors cause latitudinal as well as seasonal biases in simulated stratospheric and, hence, column-averaged CH4 mixing ratios (XCH4). Such a model bias corresponds to an overestimation of arctic and mid-latitude CH4 emissions if inversion studies do not apply an ad hoc bias correction before inverting fluxes from XCH4 observations.
A. Inness, A.-M. Blechschmidt, I. Bouarar, S. Chabrillat, M. Crepulja, R. J. Engelen, H. Eskes, J. Flemming, A. Gaudel, F. Hendrick, V. Huijnen, L. Jones, J. Kapsomenakis, E. Katragkou, A. Keppens, B. Langerock, M. de Mazière, D. Melas, M. Parrington, V. H. Peuch, M. Razinger, A. Richter, M. G. Schultz, M. Suttie, V. Thouret, M. Vrekoussis, A. Wagner, and C. Zerefos
Atmos. Chem. Phys., 15, 5275–5303, https://doi.org/10.5194/acp-15-5275-2015, https://doi.org/10.5194/acp-15-5275-2015, 2015
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The paper presents results from data assimilation studies with the new Composition-IFS model developed in the MACC project. This system was used in MACC to produce daily analyses and 5-day forecasts of atmospheric composition and is now run daily in the EU’s Copernicus Atmosphere Monitoring Service. The paper looks at the quality of the CO, O3 and NO2 analysis fields obtained with this system, comparing them against observations, a control run and an older version of the model.
B. Langerock, M. De Mazière, F. Hendrick, C. Vigouroux, F. Desmet, B. Dils, and S. Niemeijer
Geosci. Model Dev., 8, 911–921, https://doi.org/10.5194/gmd-8-911-2015, https://doi.org/10.5194/gmd-8-911-2015, 2015
C. Vigouroux, T. Blumenstock, M. Coffey, Q. Errera, O. García, N. B. Jones, J. W. Hannigan, F. Hase, B. Liley, E. Mahieu, J. Mellqvist, J. Notholt, M. Palm, G. Persson, M. Schneider, C. Servais, D. Smale, L. Thölix, and M. De Mazière
Atmos. Chem. Phys., 15, 2915–2933, https://doi.org/10.5194/acp-15-2915-2015, https://doi.org/10.5194/acp-15-2915-2015, 2015
A. Laeng, U. Grabowski, T. von Clarmann, G. Stiller, N. Glatthor, M. Höpfner, S. Kellmann, M. Kiefer, A. Linden, S. Lossow, V. Sofieva, I. Petropavlovskikh, D. Hubert, T. Bathgate, P. Bernath, C. D. Boone, C. Clerbaux, P. Coheur, R. Damadeo, D. Degenstein, S. Frith, L. Froidevaux, J. Gille, K. Hoppel, M. McHugh, Y. Kasai, J. Lumpe, N. Rahpoe, G. Toon, T. Sano, M. Suzuki, J. Tamminen, J. Urban, K. Walker, M. Weber, and J. Zawodny
Atmos. Meas. Tech., 7, 3971–3987, https://doi.org/10.5194/amt-7-3971-2014, https://doi.org/10.5194/amt-7-3971-2014, 2014
T. Wang, F. Hendrick, P. Wang, G. Tang, K. Clémer, H. Yu, C. Fayt, C. Hermans, C. Gielen, J.-F. Müller, G. Pinardi, N. Theys, H. Brenot, and M. Van Roozendael
Atmos. Chem. Phys., 14, 11149–11164, https://doi.org/10.5194/acp-14-11149-2014, https://doi.org/10.5194/acp-14-11149-2014, 2014
K. M. Saad, D. Wunch, G. C. Toon, P. Bernath, C. Boone, B. Connor, N. M. Deutscher, D. W. T. Griffith, R. Kivi, J. Notholt, C. Roehl, M. Schneider, V. Sherlock, and P. O. Wennberg
Atmos. Meas. Tech., 7, 2907–2918, https://doi.org/10.5194/amt-7-2907-2014, https://doi.org/10.5194/amt-7-2907-2014, 2014
R. Van Malderen, H. Brenot, E. Pottiaux, S. Beirle, C. Hermans, M. De Mazière, T. Wagner, H. De Backer, and C. Bruyninx
Atmos. Meas. Tech., 7, 2487–2512, https://doi.org/10.5194/amt-7-2487-2014, https://doi.org/10.5194/amt-7-2487-2014, 2014
D. Fu, T. J. Pongetti, J.-F. L. Blavier, T. J. Crawford, K. S. Manatt, G. C. Toon, K. W. Wong, and S. P. Sander
Atmos. Meas. Tech., 7, 713–729, https://doi.org/10.5194/amt-7-713-2014, https://doi.org/10.5194/amt-7-713-2014, 2014
J.-T. Lin, R. V. Martin, K. F. Boersma, M. Sneep, P. Stammes, R. Spurr, P. Wang, M. Van Roozendael, K. Clémer, and H. Irie
Atmos. Chem. Phys., 14, 1441–1461, https://doi.org/10.5194/acp-14-1441-2014, https://doi.org/10.5194/acp-14-1441-2014, 2014
E. Mahieu, R. Zander, G. C. Toon, M. K. Vollmer, S. Reimann, J. Mühle, W. Bader, B. Bovy, B. Lejeune, C. Servais, P. Demoulin, G. Roland, P. F. Bernath, C. D. Boone, K. A. Walker, and P. Duchatelet
Atmos. Meas. Tech., 7, 333–344, https://doi.org/10.5194/amt-7-333-2014, https://doi.org/10.5194/amt-7-333-2014, 2014
F. Hendrick, J.-F. Müller, K. Clémer, P. Wang, M. De Mazière, C. Fayt, C. Gielen, C. Hermans, J. Z. Ma, G. Pinardi, T. Stavrakou, T. Vlemmix, and M. Van Roozendael
Atmos. Chem. Phys., 14, 765–781, https://doi.org/10.5194/acp-14-765-2014, https://doi.org/10.5194/acp-14-765-2014, 2014
F. Hase, B. J. Drouin, C. M. Roehl, G. C. Toon, P. O. Wennberg, D. Wunch, T. Blumenstock, F. Desmet, D. G. Feist, P. Heikkinen, M. De Mazière, M. Rettinger, J. Robinson, M. Schneider, V. Sherlock, R. Sussmann, Y. Té, T. Warneke, and C. Weinzierl
Atmos. Meas. Tech., 6, 3527–3537, https://doi.org/10.5194/amt-6-3527-2013, https://doi.org/10.5194/amt-6-3527-2013, 2013
J.-L. Baray, Y. Courcoux, P. Keckhut, T. Portafaix, P. Tulet, J.-P. Cammas, A. Hauchecorne, S. Godin Beekmann, M. De Mazière, C. Hermans, F. Desmet, K. Sellegri, A. Colomb, M. Ramonet, J. Sciare, C. Vuillemin, C. Hoareau, D. Dionisi, V. Duflot, H. Vérèmes, J. Porteneuve, F. Gabarrot, T. Gaudo, J.-M. Metzger, G. Payen, J. Leclair de Bellevue, C. Barthe, F. Posny, P. Ricaud, A. Abchiche, and R. Delmas
Atmos. Meas. Tech., 6, 2865–2877, https://doi.org/10.5194/amt-6-2865-2013, https://doi.org/10.5194/amt-6-2865-2013, 2013
S. Vandenbussche, S. Kochenova, A. C. Vandaele, N. Kumps, and M. De Mazière
Atmos. Meas. Tech., 6, 2577–2591, https://doi.org/10.5194/amt-6-2577-2013, https://doi.org/10.5194/amt-6-2577-2013, 2013
D. Wunch, P. O. Wennberg, J. Messerschmidt, N. C. Parazoo, G. C. Toon, N. M. Deutscher, G. Keppel-Aleks, C. M. Roehl, J. T. Randerson, T. Warneke, and J. Notholt
Atmos. Chem. Phys., 13, 9447–9459, https://doi.org/10.5194/acp-13-9447-2013, https://doi.org/10.5194/acp-13-9447-2013, 2013
Y. Yoshida, N. Kikuchi, I. Morino, O. Uchino, S. Oshchepkov, A. Bril, T. Saeki, N. Schutgens, G. C. Toon, D. Wunch, C. M. Roehl, P. O. Wennberg, D. W. T. Griffith, N. M. Deutscher, T. Warneke, J. Notholt, J. Robinson, V. Sherlock, B. Connor, M. Rettinger, R. Sussmann, P. Ahonen, P. Heikkinen, E. Kyrö, J. Mendonca, K. Strong, F. Hase, S. Dohe, and T. Yokota
Atmos. Meas. Tech., 6, 1533–1547, https://doi.org/10.5194/amt-6-1533-2013, https://doi.org/10.5194/amt-6-1533-2013, 2013
V. Duflot, D. Hurtmans, L. Clarisse, Y. R'honi, C. Vigouroux, M. De Mazière, E. Mahieu, C. Servais, C. Clerbaux, and P.-F. Coheur
Atmos. Meas. Tech., 6, 917–925, https://doi.org/10.5194/amt-6-917-2013, https://doi.org/10.5194/amt-6-917-2013, 2013
C. Frankenberg, D. Wunch, G. Toon, C. Risi, R. Scheepmaker, J.-E. Lee, P. Wennberg, and J. Worden
Atmos. Meas. Tech., 6, 263–274, https://doi.org/10.5194/amt-6-263-2013, https://doi.org/10.5194/amt-6-263-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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 with the March 2022 version of MOCAGE
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
Tightening-up methane plume source rate estimation in EnMAP and PRISMA images
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
Improved detection of global NOx emissions from shipping in Sentinel-5P TROPOMI data
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
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
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
Mickaël Bacles, Jonathan Améric, and Vincent Guidard
Atmos. Meas. Tech., 18, 2659–2680, https://doi.org/10.5194/amt-18-2659-2025, https://doi.org/10.5194/amt-18-2659-2025, 2025
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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 chemistry transport model developed at Météo-France by assimilated infrared and ultraviolet satellite instruments. We focus on the eruption event of the La Soufrière Saint Vincent volcano in April 2021. The combined assimilation of these observations always leads to better analyses and forecasts.
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.
Elyes Ouerghi, Thibaud Ehret, Gabriele Facciolo, Enric Meinhardt, Rodolphe Marion, and Jean-Michel Morel
EGUsphere, https://doi.org/10.5194/egusphere-2025-1075, https://doi.org/10.5194/egusphere-2025-1075, 2025
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Reducing methane emissions is essential to tackle climate change. In this paper, we introduce MetFluxNet, a deep learning model for methane plume source rate estimation. This model is trained on a new synthetic dataset designed to avoid network overfit. MetFluxNet can accurately estimate low source rates even in the case of heterogeneous backgrounds. To demonstrate its reliability for real-world plume estimation, we validated its predictions on real plumes with known source rates.
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.
Miriam Latsch, Andreas Richter, John P. Burrows, and Hartmut Bösch
EGUsphere, https://doi.org/10.5194/egusphere-2025-107, https://doi.org/10.5194/egusphere-2025-107, 2025
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This study presents our advanced methods to better detect ship-related nitrogen dioxide (NO2) emissions in TROPOMI satellite data. By applying filtering techniques, we identify numerous global shipping routes, including previously undetectable ones, and emissions from offshore platforms. Additionally, we compare the filtered satellite data with CAMS global model data to estimate the differences between observed and modelled NO2 emissions.
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.
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.
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).
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Short summary
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).
Solar absorption spectra near 2967 cm−1 recorded by a ground-based FTIR with a high spectral...
