Articles | Volume 23, issue 14
https://doi.org/10.5194/acp-23-8039-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-8039-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Jul 2023
Research article |
| 19 Jul 2023
East Asian methane emissions inferred from high-resolution inversions of GOSAT and TROPOMI observations: a comparative and evaluative analysis
Ruosi Liang
College of Environmental and Resource Sciences, Zhejiang University,
Hangzhou, Zhejiang 310058, China
Key Laboratory of Coastal Environment and Resources of Zhejiang
Province, School of Engineering, Westlake University, Hangzhou, Zhejiang
310030, China
Institute of Advanced Technology, Westlake Institute for Advanced
Study, Hangzhou, Zhejiang 310024, China
Yuzhong Zhang
CORRESPONDING AUTHOR
Key Laboratory of Coastal Environment and Resources of Zhejiang
Province, School of Engineering, Westlake University, Hangzhou, Zhejiang
310030, China
Institute of Advanced Technology, Westlake Institute for Advanced
Study, Hangzhou, Zhejiang 310024, China
Wei Chen
College of Environmental and Resource Sciences, Zhejiang University,
Hangzhou, Zhejiang 310058, China
Key Laboratory of Coastal Environment and Resources of Zhejiang
Province, School of Engineering, Westlake University, Hangzhou, Zhejiang
310030, China
Institute of Advanced Technology, Westlake Institute for Advanced
Study, Hangzhou, Zhejiang 310024, China
Peixuan Zhang
Key Laboratory of Coastal Environment and Resources of Zhejiang
Province, School of Engineering, Westlake University, Hangzhou, Zhejiang
310030, China
Institute of Advanced Technology, Westlake Institute for Advanced
Study, Hangzhou, Zhejiang 310024, China
Fudan University, Shanghai 200433, China
Jingran Liu
College of Environmental and Resource Sciences, Zhejiang University,
Hangzhou, Zhejiang 310058, China
Key Laboratory of Coastal Environment and Resources of Zhejiang
Province, School of Engineering, Westlake University, Hangzhou, Zhejiang
310030, China
Institute of Advanced Technology, Westlake Institute for Advanced
Study, Hangzhou, Zhejiang 310024, China
Cuihong Chen
Center for Satellite Application on Ecology and Environment, Ministry
of Ecology and Environment of China, Beijing 100094, China
Huiqin Mao
Center for Satellite Application on Ecology and Environment, Ministry
of Ecology and Environment of China, Beijing 100094, China
Guofeng Shen
Laboratory for Earth Surface Processes, College of Urban and
Environmental Sciences, Peking University, Beijing 100871, China
Department of Marine Earth and Atmospheric Sciences, North Carolina
State University, Raleigh, NC 27607, USA
Zichong Chen
School of Engineering and Applied Science, Harvard University,
Cambridge, MA, USA
Minqiang Zhou
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing
100029, China
Pucai Wang
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing
100029, China
University of Chinese Academy of Sciences, Beijing 100049, China
Robert J. Parker
National Centre for Earth Observation, University of Leicester,
Leicester, UK
Earth Observation Science, School of Physics and Astronomy,
University of Leicester, Leicester, UK
Hartmut Boesch
National Centre for Earth Observation, University of Leicester,
Leicester, UK
Earth Observation Science, School of Physics and Astronomy,
University of Leicester, Leicester, UK
Alba Lorente
SRON Netherlands Institute for Space Research, Utrecht, the
Netherlands
Joannes D. Maasakkers
SRON Netherlands Institute for Space Research, Utrecht, the
Netherlands
Ilse Aben
SRON Netherlands Institute for Space Research, Utrecht, the
Netherlands
Related authors
Xinchun Xie, Yuzhong Zhang, Ruosi Liang, and Xuan Wang
Atmos. Chem. Phys., 25, 13547–13561, https://doi.org/10.5194/acp-25-13547-2025, https://doi.org/10.5194/acp-25-13547-2025, 2025
Short summary
Short summary
Brown carbon (BrC), mainly from biomass burning, absorbs short-wavelength sunlight and affects climate and atmospheric chemistry. This study implemented an improved parameterization of BrC bleaching in a model with which BrC can survive much longer in cold, dry air, especially when lofted into the upper atmosphere by wildfires. The results reveal stronger warming effects and impacts on atmospheric oxidation, highlighting the need to consider BrC in climate and pollution control strategies.
Xiaobo Wang, Yuzhong Zhang, Tamás Bozóki, Ruosi Liang, Xinchun Xie, Shutao Zhao, Rui Wang, Yujia Zhao, and Shuai Sun
Atmos. Chem. Phys., 25, 8929–8942, https://doi.org/10.5194/acp-25-8929-2025, https://doi.org/10.5194/acp-25-8929-2025, 2025
Short summary
Short summary
Schumann resonance observations are used to parameterise lightning NOx emissions to better capture global lightning trends and variability. Updated simulations reveal insignificant trends but greater variability in lightning NOx emissions, impacting tropospheric NOx, O3, and OH. Lightning generally counteracts non-lightning factors, reducing the inter-annual variability of tropospheric O3 and OH. Variations in global lightning play an important role in understanding the atmospheric methane budget.
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
Short summary
Short summary
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.
Hantao Wang, Kazuyuki Miyazaki, Haitong Zhe Sun, Zhen Qu, Xiang Liu, Antje Inness, Martin Schultz, Sabine Schröder, Marc Serre, and J. Jason West
Atmos. Chem. Phys., 25, 15969–15990, https://doi.org/10.5194/acp-25-15969-2025, https://doi.org/10.5194/acp-25-15969-2025, 2025
Short summary
Short summary
We compare six datasets of global ground-level ozone, developed using geostatistical, machine learning, or reanalysis methods. The datasets show important differences from one another in ozone magnitude, greater than 5 ppb, and trends, globally and regionally. Compared with measurements, performance varies among datasets, and most overestimate ozone, particularly at lower concentrations. These differences among datasets highlight uncertainties for applications to health and other impacts.
Oliver Schneising, Heinrich Bovensmann, Michael Buchwitz, Matthias Buschmann, Nicholas M. Deutscher, David W. T. Griffith, Jonas Hachmeister, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Hirofumi Ohyama, Christof Petri, Maximilian Reuter, John Robinson, Coleen Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Wei Wang, Thorsten Warneke, Damien Weidmann, Debra Wunch, Minqiang Zhou, and Hartmut Bösch
EGUsphere, https://doi.org/10.5194/egusphere-2025-5422, https://doi.org/10.5194/egusphere-2025-5422, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
We present an improved version of the TROPOMI/WFMD algorithm for the simultaneous retrieval of atmospheric methane and carbon monoxide from satellite observations. The updated data product combines higher data yield with better precision and accuracy, expanding its suitability for a wider range of scientific applications. These substantial advances are mainly due to refined quality filtering, enabling more reliable identification of cloudy scenes and mitigating specific aerosol-related issues.
Sven Krautwurst, Christian Fruck, Sebastian Wolff, Jakob Borchardt, Oke Huhs, Konstantin Gerilowski, Michał Gałkowski, Christoph Kiemle, Mathieu Quatrevalet, Martin Wirth, Christian Mallaun, John P. Burrows, Christoph Gerbig, Andreas Fix, Hartmut Bösch, and Heinrich Bovensmann
Atmos. Chem. Phys., 25, 14669–14702, https://doi.org/10.5194/acp-25-14669-2025, https://doi.org/10.5194/acp-25-14669-2025, 2025
Short summary
Short summary
Anomalously high CH4 emissions from landfills in Madrid, Spain, have been observed by satellite measurements in recent years. Our investigations of these waste facilities, using passive and active airborne remote sensing measurements, confirm these high emission rates with values of up to 13 th−1 during the overflight and show excellent agreement between the two techniques. A large fraction of the emissions is attributed to active landfill sites.
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
Atmos. Meas. Tech., 18, 6093–6123, https://doi.org/10.5194/amt-18-6093-2025, https://doi.org/10.5194/amt-18-6093-2025, 2025
Short summary
Short summary
The Greenhouse Gases Observing Satellite-2 (GOSAT-2) is a satellite dedicated to measuring concentrations of greenhouse gases from space. Since its launch, the increase of CH4 and CO2 concentrations in the atmosphere is clear. The datasets obtained from GOSAT-2 are used in the Copernicus atmospheric services to monitor the climate, in light of the Paris Agreement. Here we present robust datasets of these gases from GOSAT-2, including a novel machine learning approach to data quality filtering.
Xinchun Xie, Yuzhong Zhang, Ruosi Liang, and Xuan Wang
Atmos. Chem. Phys., 25, 13547–13561, https://doi.org/10.5194/acp-25-13547-2025, https://doi.org/10.5194/acp-25-13547-2025, 2025
Short summary
Short summary
Brown carbon (BrC), mainly from biomass burning, absorbs short-wavelength sunlight and affects climate and atmospheric chemistry. This study implemented an improved parameterization of BrC bleaching in a model with which BrC can survive much longer in cold, dry air, especially when lofted into the upper atmosphere by wildfires. The results reveal stronger warming effects and impacts on atmospheric oxidation, highlighting the need to consider BrC in climate and pollution control strategies.
Jiaxin Wang, Sieglinde Callewaert, Minqiang Zhou, Filip Desmet, Sébastien Conil, Michel Ramonet, Pucai Wang, and Martine De Mazière
EGUsphere, https://doi.org/10.5194/egusphere-2025-4537, https://doi.org/10.5194/egusphere-2025-4537, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We used a regional atmospheric transport model to simulate carbon dioxide mole fractions over Western Europe. The results show the importance of anthropogenic emission configurations, particularly near large emission sources, as well as the necessity of improving biogenic flux simulations. These findings contribute to enhancing the accuracy of carbon dioxide modeling and carbon budget inversions.
Peter Somkuti, Gregory McGarragh, Christopher O'Dell, Antonio Di Noia, Leif Vogel, Sean Crowell, Lesley E. Ott, and Hartmut Bösch
Atmos. Meas. Tech., 18, 4647–4663, https://doi.org/10.5194/amt-18-4647-2025, https://doi.org/10.5194/amt-18-4647-2025, 2025
Short summary
Short summary
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.
Minqiang Zhou, Yilong Wang, Minzheng Duan, Xiangjun Tian, Jinzhi Ding, Jianrong Bi, Yaoming Ma, Weiqiang Ma, and Zhenhua Xi
Atmos. Meas. Tech., 18, 4311–4324, https://doi.org/10.5194/amt-18-4311-2025, https://doi.org/10.5194/amt-18-4311-2025, 2025
Short summary
Short summary
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.
Sieglinde Callewaert, Minqiang Zhou, Bavo Langerock, Pucai Wang, Ting Wang, Emmanuel Mahieu, and Martine De Mazière
EGUsphere, https://doi.org/10.5194/egusphere-2025-3959, https://doi.org/10.5194/egusphere-2025-3959, 2025
Short summary
Short summary
We investigated changes in carbon dioxide levels at a suburban site in China using ground-based measurements, remote sensing, and an atmospheric model. The model matched many observed patterns but showed nighttime and background errors. We identified the main human and natural sources and sinks, offering insights to improve future greenhouse gas monitoring and climate modelling.
Huirong Yang, Kai Wu, Huizhong Shen, Greet Janssens-Maenhout, Monica Crippa, Diego Guizzardi, and Minqiang Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2025-3914, https://doi.org/10.5194/egusphere-2025-3914, 2025
Short summary
Short summary
We compare six major anthropogenic CO2 emission inventories in China during the period 2000–2023 to assess emission trends and uncertainties. National emissions show a clear three‑phase pattern, with uncertainties below 5 % (1σ) at the national scale but much higher at the provincial level (10–50 %, 1σ). High-emission regions often have the largest uncertainties. Our findings support more accurate emission estimates and the verification emission reduction policies.
Sieglinde Callewaert, Minqiang Zhou, Bavo Langerock, Pucai Wang, Ting Wang, Emmanuel Mahieu, and Martine De Mazière
Atmos. Chem. Phys., 25, 9519–9544, https://doi.org/10.5194/acp-25-9519-2025, https://doi.org/10.5194/acp-25-9519-2025, 2025
Short summary
Short summary
We used an atmospheric transport model and satellite data to study CH4 observations in 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 kinds of measurements and helps us to better understand CH4 variability in the region.
Xiaobo Wang, Yuzhong Zhang, Tamás Bozóki, Ruosi Liang, Xinchun Xie, Shutao Zhao, Rui Wang, Yujia Zhao, and Shuai Sun
Atmos. Chem. Phys., 25, 8929–8942, https://doi.org/10.5194/acp-25-8929-2025, https://doi.org/10.5194/acp-25-8929-2025, 2025
Short summary
Short summary
Schumann resonance observations are used to parameterise lightning NOx emissions to better capture global lightning trends and variability. Updated simulations reveal insignificant trends but greater variability in lightning NOx emissions, impacting tropospheric NOx, O3, and OH. Lightning generally counteracts non-lightning factors, reducing the inter-annual variability of tropospheric O3 and OH. Variations in global lightning play an important role in understanding the atmospheric methane budget.
Gaia Pinardi, Martina M. Friedrich, Corinne Vigouroux, Bavo Langerock, Isabelle De Smedt, Caroline Fayt, Christian Hermans, Steffen Beirle, Thomas Wagner, Minqiang Zhou, Ting Wang, Pucai Wang, Martine De Mazière, and Michel Van Roozendael
EGUsphere, https://doi.org/10.5194/egusphere-2025-3320, https://doi.org/10.5194/egusphere-2025-3320, 2025
Short summary
Short summary
MultiAXis Differential Optical Absorption Spectroscopy, direct sun DOAS, and Fourier Transform InfraRed are key for formaldehyde satellite validation. We show a -20% bias for MAX-DOAS vertical column data versus direct sun UV and IR measurement at Xianghe, China. Adjustments for vertical sensitivities and a priori profiles reduce differences to less than 2.5%. Using chemical transport models as a priori further decreases the bias, indicating possible improvements for current MAX-DOAS retrievals.
Wei Feng, Xiangyu Zhang, Zhijuan Shao, Guofeng Shen, Hong Liao, Yuhang Wang, and Mingjie Xie
EGUsphere, https://doi.org/10.5194/egusphere-2025-2106, https://doi.org/10.5194/egusphere-2025-2106, 2025
Short summary
Short summary
In this work, the relative differences in particle concentrations of water-soluble organic molecular markers (WSOMMs) between the collocated filter samples represent the uncertainties in the measurements. The comparisons between the measurements of chemically treated and untreated backup filter samples indicate that the WSOMMs detected on the backup filters may originate from heterogeneous reactions on the filter surfaces, but are not caused by the adsorption of gaseous molecules.
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
Atmos. Chem. Phys., 25, 7829–7862, https://doi.org/10.5194/acp-25-7829-2025, https://doi.org/10.5194/acp-25-7829-2025, 2025
Short summary
Short summary
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.
Aurélien Sicsik-Paré, Audrey Fortems-Cheiney, Isabelle Pison, Grégoire Broquet, Alvin Opler, Elise Potier, Adrien Martinez, Oliver Schneising, Michael Buchwitz, Joannes D. Maasakkers, Tobias Borsdorff, and Antoine Berchet
EGUsphere, https://doi.org/10.5194/egusphere-2025-2622, https://doi.org/10.5194/egusphere-2025-2622, 2025
Short summary
Short summary
Assimilating satellite observations from TROPOMI provides top-down quantification of regional methane emissions. This study compares European emissions in 2019 estimated from the inversion of three TROPOMI datasets. We find inconsistencies in national budgets and spatial patterns, with no product clearly superior. We disentangle drivers of the differences, highlighting the impact of differences in coverage, observations and associated errors on the consistency of methane emission estimates.
Hannah Nesser, Kevin W. Bowman, Matthew D. Thill, Daniel J. Varon, Cynthia A. Randles, Ashutosh Tewari, Felipe J. Cardoso-Saldaña, Emily Reidy, Joannes D. Maasakkers, and Daniel J. Jacob
EGUsphere, https://doi.org/10.5194/egusphere-2025-2850, https://doi.org/10.5194/egusphere-2025-2850, 2025
Short summary
Short summary
Regional analyses of atmospheric trace gases can improve knowledge of fluxes and their trends at high resolution but rely on the specification of boundary conditions at the domain edges. Biases in the often-uncertain boundary conditions propagate to the inferred fluxes. We develop a framework to explain how errors in the boundary conditions influence the optimized fluxes, derive two metrics to estimate this influence, and compare two methods to correct for the biases.
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
Short summary
Short summary
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.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
Short summary
Short summary
Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
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
Short summary
Short summary
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.
Marielle Saunois, Adrien Martinez, Benjamin Poulter, Zhen Zhang, Peter A. Raymond, Pierre Regnier, Josep G. Canadell, Robert B. Jackson, Prabir K. Patra, Philippe Bousquet, Philippe Ciais, Edward J. Dlugokencky, Xin Lan, George H. Allen, David Bastviken, David J. Beerling, Dmitry A. Belikov, Donald R. Blake, Simona Castaldi, Monica Crippa, Bridget R. Deemer, Fraser Dennison, Giuseppe Etiope, Nicola Gedney, Lena Höglund-Isaksson, Meredith A. Holgerson, Peter O. Hopcroft, Gustaf Hugelius, Akihiko Ito, Atul K. Jain, Rajesh Janardanan, Matthew S. Johnson, Thomas Kleinen, Paul B. Krummel, Ronny Lauerwald, Tingting Li, Xiangyu Liu, Kyle C. McDonald, Joe R. Melton, Jens Mühle, Jurek Müller, Fabiola Murguia-Flores, Yosuke Niwa, Sergio Noce, Shufen Pan, Robert J. Parker, Changhui Peng, Michel Ramonet, William J. Riley, Gerard Rocher-Ros, Judith A. Rosentreter, Motoki Sasakawa, Arjo Segers, Steven J. Smith, Emily H. Stanley, Joël Thanwerdas, Hanqin Tian, Aki Tsuruta, Francesco N. Tubiello, Thomas S. Weber, Guido R. van der Werf, Douglas E. J. Worthy, Yi Xi, Yukio Yoshida, Wenxin Zhang, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
Short summary
Short summary
Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Simon Laffoy, Marco Vountas, Linlu Mei, and Hartmut Bösch
EGUsphere, https://doi.org/10.5194/egusphere-2025-1282, https://doi.org/10.5194/egusphere-2025-1282, 2025
Short summary
Short summary
Aerosol are particles in the atmosphere such as dust, salt, soot and sulfates. They may be measured by applying algorithms to satellite images of the Earth. We attempt to apply data from the new Environmental Mapping and Analysis Program (EnMAP) satellite to the existing XBAER algorithm, which was previously applied to data from the Ocean Land and Colour Instrument (OLCI) satellite. This paper compares the satellite inputs and aerosol outputs of the XBAER algorithm and finds good results.
Ulrike Stöffelmair, Thomas Popp, Marco Vountas, and Hartmut Bösch
Atmos. Meas. Tech., 18, 2005–2020, https://doi.org/10.5194/amt-18-2005-2025, https://doi.org/10.5194/amt-18-2005-2025, 2025
Short summary
Short summary
Aerosol composition has a large influence on the climate system. This study uses realistic simulated scenarios to look at the information content of a combination of three satellite-based instruments (SLSTR, IASI and GOME-2). It shows that it is possible to retrieve 6 to 15 different aerosol components in addition to the aerosol optical depth (AOD) and different surface parameters. The results are used for the development of a synergistic multi-sensor retrieval algorithm.
Junyue Yang, Zhengning Xu, Zheng Xia, Xiangyu Pei, Yunye Yang, Botian Qiu, Shuang Zhao, Yuzhong Zhang, and Zhibin Wang
Atmos. Chem. Phys., 25, 4571–4585, https://doi.org/10.5194/acp-25-4571-2025, https://doi.org/10.5194/acp-25-4571-2025, 2025
Short summary
Short summary
Mobile CH4 measurements were conducted at a wastewater treatment plant in Hangzhou in the summer and winter of 2023. A multi-source Gaussian plume model, combined with a genetic algorithm inversion framework, was used to locate major CH4 sources at the plant and quantify emissions. Results indicate that the summer CH4 emissions (603.33 ± 152.66 t a-1) were 2.8 times as high as inventory values, and winter values (418.95 ± 187.59 t a-1) were twice as high. The main sources were the screen and primary clarifier.
Shutao Zhao, Yuzhong Zhang, Shuang Zhao, Xinlu Wang, and Daniel J. Varon
Atmos. Chem. Phys., 25, 4035–4052, https://doi.org/10.5194/acp-25-4035-2025, https://doi.org/10.5194/acp-25-4035-2025, 2025
Short summary
Short summary
We target the challenge of detecting methane super-emitters in oil and gas fields, which is critical for mitigating climate change. Traditional satellite-based detectors struggle due to interference from complex surfaces. We developed a novel method using deep transfer learning that improves detection efficiency and accuracy by reducing artifacts and adapting methane knowledge to different regions. Application revealed significant methane emissions, demonstrating the potential of our method.
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
Short summary
Short summary
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.
Elise Penn, Daniel J. Jacob, Zichong Chen, James D. East, Melissa P. Sulprizio, Lori Bruhwiler, Joannes D. Maasakkers, Hannah Nesser, Zhen Qu, Yuzhong Zhang, and John Worden
Atmos. Chem. Phys., 25, 2947–2965, https://doi.org/10.5194/acp-25-2947-2025, https://doi.org/10.5194/acp-25-2947-2025, 2025
Short summary
Short summary
The hydroxyl radical (OH) destroys many air pollutants, including methane. Global-mean OH cannot be directly measured, and thus it is inferred with the methyl chloroform (MCF) proxy. MCF is decreasing, and a replacement is needed. We use satellite observations of methane in two spectral ranges as a proxy for OH. We find shortwave infrared observations can characterize yearly OH and its seasonality but not the latitudinal distribution. Thermal infrared observations add little information.
Takashi Sekiya, Emanuele Emili, Kazuyuki Miyazaki, Antje Inness, Zhen Qu, R. Bradley Pierce, Dylan Jones, Helen Worden, William Y. Y. Cheng, Vincent Huijnen, and Gerbrand Koren
Atmos. Chem. Phys., 25, 2243–2268, https://doi.org/10.5194/acp-25-2243-2025, https://doi.org/10.5194/acp-25-2243-2025, 2025
Short summary
Short summary
Five global chemical reanalysis datasets were used to assess the relative impacts of assimilating satellite ozone and its precursor measurements on tropospheric ozone analyses for 2010. The multiple reanalysis system comparison allows an evaluation of the dependency of the impacts on different reanalysis systems. The results suggested the importance of satellite ozone and its precursor measurements for improving ozone analysis in the whole troposphere, with varying magnitudes among the systems.
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
Short summary
Short summary
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.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, Ivar R. van der Velde, and Ilse Aben
Atmos. Chem. Phys., 25, 555–574, https://doi.org/10.5194/acp-25-555-2025, https://doi.org/10.5194/acp-25-555-2025, 2025
Short summary
Short summary
The production of steel coincides with large emissions of greenhouse gases and air pollutants including carbon monoxide. European facilities are required to report their emissions, which are estimated using a variety of methods. We evaluate these estimates using carbon monoxide concentrations measured via satellite. We find generally good agreement between our values and those reported but also identify some uncertainties, showing that satellites can provide insights into these emissions.
Sarah E. Hancock, Daniel J. Jacob, Zichong Chen, Hannah Nesser, Aaron Davitt, Daniel J. Varon, Melissa P. Sulprizio, Nicholas Balasus, Lucas A. Estrada, María Cazorla, Laura Dawidowski, Sebastián Diez, James D. East, Elise Penn, Cynthia A. Randles, John Worden, Ilse Aben, Robert J. Parker, and Joannes D. Maasakkers
Atmos. Chem. Phys., 25, 797–817, https://doi.org/10.5194/acp-25-797-2025, https://doi.org/10.5194/acp-25-797-2025, 2025
Short summary
Short summary
We quantify 2021 methane emissions in South America at up to 25 km × 25 km resolution using satellite methane observations. We find a 55 % upward adjustment to anthropogenic emission inventories, including those reported to the UN Framework Convention on Climate Change under the Paris Agreement. Our estimates match inventories for Brazil, Bolivia, and Paraguay but are much higher for other countries. Livestock emissions (65 % of anthropogenic emissions) show the largest discrepancies.
Dylan Jones, Lucas Prates, Zhen Qu, William Cheng, Kazuyuki Miyazaki, Takashi Sekiya, Antje Inness, Rajesh Kumar, Xiao Tang, Helen Worden, Gerbrand Koren, and Vincent Huijen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3759, https://doi.org/10.5194/egusphere-2024-3759, 2025
Short summary
Short summary
We evaluate five chemical reanalysis products to assess their potential to provide useful information on tropospheric ozone variability. We find that the reanalyses produce consistent information on ozone variations in the free troposphere, but have large discrepancies at the surface. The results suggests that improvements in the reanalyses are needed to better exploit the assimilated observations to enhance the utility of the reanalysis products at the surface.
Minqiang Zhou, Pucai Wang, Bart Dils, Bavo Langerock, Geoff Toon, Christian Hermans, Weidong Nan, Qun Cheng, and Martine De Mazière
Atmos. Meas. Tech., 17, 6385–6396, https://doi.org/10.5194/amt-17-6385-2024, https://doi.org/10.5194/amt-17-6385-2024, 2024
Short summary
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).
Neil Humpage, Hartmut Boesch, William Okello, Jia Chen, Florian Dietrich, Mark F. Lunt, Liang Feng, Paul I. Palmer, and Frank Hase
Atmos. Meas. Tech., 17, 5679–5707, https://doi.org/10.5194/amt-17-5679-2024, https://doi.org/10.5194/amt-17-5679-2024, 2024
Short summary
Short summary
We used a Bruker EM27/SUN spectrometer within an automated weatherproof enclosure to measure greenhouse gas column concentrations over a 3-month period in Jinja, Uganda. The portability of the EM27/SUN allows us to evaluate satellite and model data in locations not covered by traditional validation networks. This is of particular value in tropical Africa, where extensive terrestrial ecosystems are a significant store of carbon and play a key role in the atmospheric budgets of CO2 and CH4.
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
Short summary
Short summary
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.
Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, and Hartmut Bösch
Atmos. Chem. Phys., 24, 7609–7621, https://doi.org/10.5194/acp-24-7609-2024, https://doi.org/10.5194/acp-24-7609-2024, 2024
Short summary
Short summary
Large quantities of CO and CO2 are emitted during conventional steel production. As satellite-based estimates of CO2 emissions at the facility level are challenging, co-emitted CO can indicate the carbon footprint of steel plants. We estimate CO emissions for German steelworks and use CO2 emissions from emissions trading data to derive a sector-specific CO/CO2 emission ratio for the steel industry; it is a prerequisite to use CO as a proxy for CO2 emissions from similar steel production sites.
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
Short summary
Short summary
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.
Brian Nathan, Joannes D. Maasakkers, Stijn Naus, Ritesh Gautam, Mark Omara, Daniel J. Varon, Melissa P. Sulprizio, Lucas A. Estrada, Alba Lorente, Tobias Borsdorff, Robert J. Parker, and Ilse Aben
Atmos. Chem. Phys., 24, 6845–6863, https://doi.org/10.5194/acp-24-6845-2024, https://doi.org/10.5194/acp-24-6845-2024, 2024
Short summary
Short summary
Venezuela's Lake Maracaibo region is notoriously hard to observe from space and features intensive oil exploitation, although production has strongly decreased in recent years. We estimate methane emissions using 2018–2020 TROPOMI satellite observations with national and regional transport models. Despite the production decrease, we find relatively constant emissions from Lake Maracaibo between 2018 and 2020, indicating that there could be large emissions from abandoned infrastructure.
Lu Zhang, Jin Li, Yaojie Li, Xinlei Liu, Zhihan Luo, Guofeng Shen, and Shu Tao
Atmos. Chem. Phys., 24, 6323–6337, https://doi.org/10.5194/acp-24-6323-2024, https://doi.org/10.5194/acp-24-6323-2024, 2024
Short summary
Short summary
Brown carbon (BrC) is related to radiative forcing and climate change. The BrC fraction from residential coal and biomass burning emissions, which were the major source of BrC, was characterized at the molecular level. The CHOS aromatic compounds explained higher light absorption efficiencies of biomass burning emissions compared to coal. The unique formulas of coal combustion aerosols were characterized by higher unsaturated compounds, and such information could be used for source appointment.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Alba Lorente, Zichong Chen, Xiao Lu, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Margaux Winter, Shuang Ma, A. Anthony Bloom, John R. Worden, Robert N. Stavins, and Cynthia A. Randles
Atmos. Chem. Phys., 24, 5069–5091, https://doi.org/10.5194/acp-24-5069-2024, https://doi.org/10.5194/acp-24-5069-2024, 2024
Short summary
Short summary
We quantify 2019 methane emissions in the contiguous US (CONUS) at a ≈ 25 km × 25 km resolution using satellite methane observations. We find a 13 % upward correction to the 2023 US Environmental Protection Agency (EPA) Greenhouse Gas Emissions Inventory (GHGI) for 2019, with large corrections to individual states, urban areas, and landfills. This may present a challenge for US climate policies and goals, many of which target significant reductions in methane emissions.
Emily Y. Li, Amir Yazdani, Ann M. Dillner, Guofeng Shen, Wyatt M. Champion, James J. Jetter, William T. Preston, Lynn M. Russell, Michael D. Hays, and Satoshi Takahama
Atmos. Meas. Tech., 17, 2401–2413, https://doi.org/10.5194/amt-17-2401-2024, https://doi.org/10.5194/amt-17-2401-2024, 2024
Short summary
Short summary
Infrared spectroscopy is a cost-effective measurement technique to characterize the chemical composition of organic aerosol emissions. This technique differentiates the organic matter emission factor from different fuel sources by their characteristic functional groups. Comparison with collocated measurements suggests that polycyclic aromatic hydrocarbon concentrations in emissions estimated by conventional chromatography may be substantially underestimated.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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).
Blanca Fuentes Andrade, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Andreas Richter, Hartmut Boesch, and John P. Burrows
Atmos. Meas. Tech., 17, 1145–1173, https://doi.org/10.5194/amt-17-1145-2024, https://doi.org/10.5194/amt-17-1145-2024, 2024
Short summary
Short summary
We developed a method to estimate CO2 emissions from localized sources, such as power plants, using satellite data and applied it to estimate CO2 emissions from the Bełchatów Power Station (Poland). As the detection of CO2 emission plumes from satellite data is difficult, we used observations of co-emitted NO2 to constrain the emission plume region. Our results agree with CO2 emission estimations based on the power-plant-generated power and emission factors.
Xiao-San Luo, Weijie Huang, Guofeng Shen, Yuting Pang, Mingwei Tang, Weijun Li, Zhen Zhao, Hanhan Li, Yaqian Wei, Longjiao Xie, and Tariq Mehmood
Atmos. Chem. Phys., 24, 1345–1360, https://doi.org/10.5194/acp-24-1345-2024, https://doi.org/10.5194/acp-24-1345-2024, 2024
Short summary
Short summary
PM2.5 are air pollutants threatening health globally, but they are a mixture of chemical compositions from many sources and result in unequal toxicity. Which composition from which source of PM2.5 as the most hazardous object is a question hindering effective pollution control policy-making. With chemical and toxicity experiments, we found automobile exhaust and coal combustion to be priority emissions with higher toxic compositions for precise air pollution control, ensuring public health.
Lee de Mora, Ranjini Swaminathan, Richard P. Allan, Jerry C. Blackford, Douglas I. Kelley, Phil Harris, Chris D. Jones, Colin G. Jones, Spencer Liddicoat, Robert J. Parker, Tristan Quaife, Jeremy Walton, and Andrew Yool
Earth Syst. Dynam., 14, 1295–1315, https://doi.org/10.5194/esd-14-1295-2023, https://doi.org/10.5194/esd-14-1295-2023, 2023
Short summary
Short summary
We investigate the flux of carbon from the atmosphere into the land surface and ocean for multiple models and over a range of future scenarios. We did this by comparing simulations after the same change in the global-mean near-surface temperature. Using this method, we show that the choice of scenario can impact the carbon allocation to the land, ocean, and atmosphere. Scenarios with higher emissions reach the same warming levels sooner, but also with relatively more carbon in the atmosphere.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Tim A. van Kempen, Tim J. Rotmans, Richard M. van Hees, Carol Bruegge, Dejian Fu, Ruud Hoogeveen, Thomas J. Pongetti, Robert Rosenberg, and Ilse Aben
Atmos. Meas. Tech., 16, 4507–4527, https://doi.org/10.5194/amt-16-4507-2023, https://doi.org/10.5194/amt-16-4507-2023, 2023
Short summary
Short summary
Validation of satellite measurements is essential for providing reliable and consistent products. In this paper, a validation method for TROPOMI-SWIR (Tropospheric Measurement Instrument in the short-wavelength infrared) is explored. TROPOMI-SWIR has been shown to be exceptionally stable, a necessity to explore the methodology. Railroad Valley, Nevada, is a prime location to perform the necessary measurements to validate the satellite measurements of TROPOMI-SWIR.
Berend J. Schuit, Joannes D. Maasakkers, Pieter Bijl, Gourav Mahapatra, Anne-Wil van den Berg, Sudhanshu Pandey, Alba Lorente, Tobias Borsdorff, Sander Houweling, Daniel J. Varon, Jason McKeever, Dylan Jervis, Marianne Girard, Itziar Irakulis-Loitxate, Javier Gorroño, Luis Guanter, Daniel H. Cusworth, and Ilse Aben
Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023, https://doi.org/10.5194/acp-23-9071-2023, 2023
Short summary
Short summary
Using two machine learning models, which were trained on TROPOMI methane satellite data, we detect 2974 methane plumes, so-called super-emitters, in 2021. We detect methane emissions globally related to urban areas or landfills, coal mining, and oil and gas production. Using our monitoring system, we identify 94 regions with frequent emissions. For 12 locations, we target high-resolution satellite instruments to enlarge and identify the exact infrastructure responsible for the emissions.
Nicholas Balasus, Daniel J. Jacob, Alba Lorente, Joannes D. Maasakkers, Robert J. Parker, Hartmut Boesch, Zichong Chen, Makoto M. Kelp, Hannah Nesser, and Daniel J. Varon
Atmos. Meas. Tech., 16, 3787–3807, https://doi.org/10.5194/amt-16-3787-2023, https://doi.org/10.5194/amt-16-3787-2023, 2023
Short summary
Short summary
We use machine learning to remove biases in TROPOMI satellite observations of atmospheric methane, with GOSAT observations serving as a reference. We find that the TROPOMI biases relative to GOSAT are related to the presence of aerosols and clouds, the surface brightness, and the specific detector that makes the observation aboard TROPOMI. The resulting blended TROPOMI+GOSAT product is more reliable for quantifying methane emissions.
Gijs Leguijt, Joannes D. Maasakkers, Hugo A. C. Denier van der Gon, Arjo J. Segers, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 23, 8899–8919, https://doi.org/10.5194/acp-23-8899-2023, https://doi.org/10.5194/acp-23-8899-2023, 2023
Short summary
Short summary
We present a fast method to evaluate carbon monoxide emissions from cities in Africa. Carbon monoxide is important for climate change in an indirect way, as it is linked to ozone, methane, and carbon dioxide. Our measurements are made with a satellite that sees the entire globe every single day. This means that we can check from space whether the current knowledge of emission rates is up to date. We make the comparison and show that the emission rates in northern Africa are underestimated.
Alice Drinkwater, Paul I. Palmer, Liang Feng, Tim Arnold, Xin Lan, Sylvia E. Michel, Robert Parker, and Hartmut Boesch
Atmos. Chem. Phys., 23, 8429–8452, https://doi.org/10.5194/acp-23-8429-2023, https://doi.org/10.5194/acp-23-8429-2023, 2023
Short summary
Short summary
Changes in atmospheric methane over the last few decades are largely unexplained. Previous studies have proposed different hypotheses to explain short-term changes in atmospheric methane. We interpret observed changes in atmospheric methane and stable isotope source signatures (2004–2020). We argue that changes over this period are part of a large-scale shift from high-northern-latitude thermogenic energy emissions to tropical biogenic emissions, particularly from North Africa and South America.
Daniel J. Varon, Daniel J. Jacob, Benjamin Hmiel, Ritesh Gautam, David R. Lyon, Mark Omara, Melissa Sulprizio, Lu Shen, Drew Pendergrass, Hannah Nesser, Zhen Qu, Zachary R. Barkley, Natasha L. Miles, Scott J. Richardson, Kenneth J. Davis, Sudhanshu Pandey, Xiao Lu, Alba Lorente, Tobias Borsdorff, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 7503–7520, https://doi.org/10.5194/acp-23-7503-2023, https://doi.org/10.5194/acp-23-7503-2023, 2023
Short summary
Short summary
We use TROPOMI satellite observations to quantify weekly methane emissions from the US Permian oil and gas basin from May 2018 to October 2020. We find that Permian emissions are highly variable, with diverse economic and activity drivers. The most important drivers during our study period were new well development and natural gas price. Permian methane intensity averaged 4.6 % and decreased by 1 % per year.
Yaqin Gao, Hongli Wang, Lingling Yuan, Shengao Jing, Bin Yuan, Guofeng Shen, Liang Zhu, Abigail Koss, Yingjie Li, Qian Wang, Dan Dan Huang, Shuhui Zhu, Shikang Tao, Shengrong Lou, and Cheng Huang
Atmos. Chem. Phys., 23, 6633–6646, https://doi.org/10.5194/acp-23-6633-2023, https://doi.org/10.5194/acp-23-6633-2023, 2023
Short summary
Short summary
A near-complete speciation of reactive organic gases from residential combustion was developed to get more insights into their atmospheric effects. Oxygenated species, higher hydrocarbons and nitrogen-containing species played larger roles in these emissions compared with common hydrocarbons. Based on the near-complete speciation, these emissions were largely underestimated, leading to more underestimation of their hydroxyl radical reactivity and secondary organic aerosol formation potential.
Zichong Chen, Daniel J. Jacob, Ritesh Gautam, Mark Omara, Robert N. Stavins, Robert C. Stowe, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Drew C. Pendergrass, and Sarah Hancock
Atmos. Chem. Phys., 23, 5945–5967, https://doi.org/10.5194/acp-23-5945-2023, https://doi.org/10.5194/acp-23-5945-2023, 2023
Short summary
Short summary
We quantify methane emissions from individual countries in the Middle East and North Africa by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We show that the ability to simply relate oil/gas emissions to activity metrics is compromised by stochastic nature of local infrastructure and management practices. We find that the industry target for oil/gas methane intensity is achievable through associated gas capture, modern infrastructure, and centralized operations.
Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien H. Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
Atmos. Meas. Tech., 16, 2627–2640, https://doi.org/10.5194/amt-16-2627-2023, https://doi.org/10.5194/amt-16-2627-2023, 2023
Short summary
Short summary
Methane emissions are responsible for a lot of the warming caused by the greenhouse effect, much of which comes from a small number of point sources. We can identify methane point sources by analysing satellite data, but it requires a lot of time invested by experts and is prone to very high errors. Here, we produce a neural network that can automatically identify methane point sources and estimate the mass of methane that is being released per hour and are able to do so with far smaller errors.
Liang Feng, Paul I. Palmer, Robert J. Parker, Mark F. Lunt, and Hartmut Bösch
Atmos. Chem. Phys., 23, 4863–4880, https://doi.org/10.5194/acp-23-4863-2023, https://doi.org/10.5194/acp-23-4863-2023, 2023
Short summary
Short summary
Our understanding of recent changes in atmospheric methane has defied explanation. Since 2007, the atmospheric growth of methane has accelerated to record-breaking values in 2020 and 2021. We use satellite observations of methane to show that (1) increasing emissions over the tropics are mostly responsible for these recent atmospheric changes, and (2) changes in the OH sink during the 2020 Covid-19 lockdown can explain up to 34% of changes in atmospheric methane for that year.
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
Short summary
Short summary
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.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, and Jochen Landgraf
Atmos. Meas. Tech., 16, 1597–1608, https://doi.org/10.5194/amt-16-1597-2023, https://doi.org/10.5194/amt-16-1597-2023, 2023
Short summary
Short summary
In the TROPOMI methane data, there are few false methane anomalies that can be misinterpreted as enhancements caused by strong emission sources. These artefacts are caused by features of the underlying surfaces that are not well characterized in the retrieval algorithm. Here we improve the representation of the surface reflectance dependency with wavelength in the forward model, removing the artificial localized CH4 enhancements found in several locations like Siberia, Australia and Algeria.
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
Short summary
Short summary
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.
Xueying Yu, Dylan B. Millet, Daven K. Henze, Alexander J. Turner, Alba Lorente Delgado, A. Anthony Bloom, and Jianxiong Sheng
Atmos. Chem. Phys., 23, 3325–3346, https://doi.org/10.5194/acp-23-3325-2023, https://doi.org/10.5194/acp-23-3325-2023, 2023
Short summary
Short summary
We combine satellite measurements with a novel downscaling method to map global methane emissions at 0.1°×0.1° resolution. These fine-scale emission estimates reveal unreported emission hotspots and shed light on the roles of agriculture, wetlands, and fossil fuels for regional methane budgets. The satellite-derived emissions point in particular to missing fossil fuel emissions in the Middle East and to a large emission underestimate in South Asia that appears to be tied to monsoon rainfall.
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
Short summary
Short summary
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.
Qianqian Zhang, K. Folkert Boersma, Bin Zhao, Henk Eskes, Cuihong Chen, Haotian Zheng, and Xingying Zhang
Atmos. Chem. Phys., 23, 551–563, https://doi.org/10.5194/acp-23-551-2023, https://doi.org/10.5194/acp-23-551-2023, 2023
Short summary
Short summary
We developed an improved superposition column model and used the latest released (v2.3.1) TROPOMI satellite NO2 observations to estimate daily city-scale NOx and CO2 emissions. The results are verified against bottom-up emissions and OCO-2 XCO2 observations. We obtained the day-to-day variation of city NOx and CO2 emissions, allowing policymakers to gain real-time information on spatial–temporal emission patterns and the effectiveness of carbon and nitrogen regulation in urban environments.
Srijana Lama, Sander Houweling, K. Folkert Boersma, Ilse Aben, Hugo A. C. Denier van der Gon, and Maarten C. Krol
Atmos. Chem. Phys., 22, 16053–16071, https://doi.org/10.5194/acp-22-16053-2022, https://doi.org/10.5194/acp-22-16053-2022, 2022
Short summary
Short summary
Hydroxyl radical (OH) is the important chemical species that determines the lifetime of some greenhouse gases and trace gases. OH plays a vital role in air pollution chemistry. OH has a short lifetime and is extremely difficult to measure directly. OH concentrations derived from the chemistry transport model (CTM) have uncertainties of >50 %. Therefore, in this study, OH is derived indirectly using satellite date in urban plumes.
Robert J. Parker, Chris Wilson, Edward Comyn-Platt, Garry Hayman, Toby R. Marthews, A. Anthony Bloom, Mark F. Lunt, Nicola Gedney, Simon J. Dadson, Joe McNorton, Neil Humpage, Hartmut Boesch, Martyn P. Chipperfield, Paul I. Palmer, and Dai Yamazaki
Biogeosciences, 19, 5779–5805, https://doi.org/10.5194/bg-19-5779-2022, https://doi.org/10.5194/bg-19-5779-2022, 2022
Short summary
Short summary
Wetlands are the largest natural source of methane, one of the most important climate gases. The JULES land surface model simulates these emissions. We use satellite data to evaluate how well JULES reproduces the methane seasonal cycle over different tropical wetlands. It performs well for most regions; however, it struggles for some African wetlands influenced heavily by river flooding. We explain the reasons for these deficiencies and highlight how future development will improve these areas.
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
Short summary
Short summary
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.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, Andre Butz, Otto P. Hasekamp, Lianghai Wu, and Jochen Landgraf
Atmos. Meas. Tech., 15, 6585–6603, https://doi.org/10.5194/amt-15-6585-2022, https://doi.org/10.5194/amt-15-6585-2022, 2022
Short summary
Short summary
The TROPOspheric Monitoring Instrument (TROPOMI) performs observations over ocean in every orbit, enhancing the monitoring capabilities of methane from space. In the sun glint geometry the mirror-like reflection at the water surface provides a signal that is high enough to retrieve methane with high accuracy and precision. We present 4 years of methane concentrations over the ocean, and we assess its quality. We also show the importance of ocean observations to quantify total CH4 emissions.
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
Short summary
Short summary
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.
Yi Cheng, Shaofei Kong, Liquan Yao, Huang Zheng, Jian Wu, Qin Yan, Shurui Zheng, Yao Hu, Zhenzhen Niu, Yingying Yan, Zhenxing Shen, Guofeng Shen, Dantong Liu, Shuxiao Wang, and Shihua Qi
Earth Syst. Sci. Data, 14, 4757–4775, https://doi.org/10.5194/essd-14-4757-2022, https://doi.org/10.5194/essd-14-4757-2022, 2022
Short summary
Short summary
This work establishes the first emission inventory of carbonaceous aerosols from cooking, fireworks, sacrificial incense, joss paper burning, and barbecue, using multi-source datasets and tested emission factors. These emissions were concentrated in specific periods and areas. Positive and negative correlations between income and emissions were revealed in urban and rural regions. The dataset will be helpful for improving modeling studies and modifying corresponding emission control policies.
Lu Shen, Ritesh Gautam, Mark Omara, Daniel Zavala-Araiza, Joannes D. Maasakkers, Tia R. Scarpelli, Alba Lorente, David Lyon, Jianxiong Sheng, Daniel J. Varon, Hannah Nesser, Zhen Qu, Xiao Lu, Melissa P. Sulprizio, Steven P. Hamburg, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 11203–11215, https://doi.org/10.5194/acp-22-11203-2022, https://doi.org/10.5194/acp-22-11203-2022, 2022
Short summary
Short summary
We use 22 months of TROPOMI satellite observations to quantity methane emissions from the oil (O) and natural gas (G) sector in the US and Canada at the scale of both individual basins as well as country-wide aggregates. We find that O/G-related methane emissions are underestimated in these inventories by 80 % for the US and 40 % for Canada, and 70 % of the underestimate in the US is from five O/G basins, including Permian, Haynesville, Anadarko, Eagle Ford, and Barnett.
Zichong Chen, Daniel J. Jacob, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Elise Penn, and Xueying Yu
Atmos. Chem. Phys., 22, 10809–10826, https://doi.org/10.5194/acp-22-10809-2022, https://doi.org/10.5194/acp-22-10809-2022, 2022
Short summary
Short summary
We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current
coal-to-gasenergy transition in China. However, this small loss rate can be misleading given China's high gas imports.
Sara Martínez-Alonso, Merritt N. Deeter, Bianca C. Baier, Kathryn McKain, Helen Worden, Tobias Borsdorff, Colm Sweeney, and Ilse Aben
Atmos. Meas. Tech., 15, 4751–4765, https://doi.org/10.5194/amt-15-4751-2022, https://doi.org/10.5194/amt-15-4751-2022, 2022
Short summary
Short summary
AirCore is a novel balloon sampling system that can measure, among others, vertical profiles of carbon monoxide (CO) from 25–30 km of altitude to near the surface. Our analyses of AirCore and satellite CO data show that AirCore profiles are suited for satellite data validation, the use of shorter aircraft vertical profiles in satellite validation results in small errors (1–3 percent points) mostly at 300 hPa and above, and the error introduced by clouds in TROPOMI land data is small (1–2 %).
Pieternel F. Levelt, Deborah C. Stein Zweers, Ilse Aben, Maite Bauwens, Tobias Borsdorff, Isabelle De Smedt, Henk J. Eskes, Christophe Lerot, Diego G. Loyola, Fabian Romahn, Trissevgeni Stavrakou, Nicolas Theys, Michel Van Roozendael, J. Pepijn Veefkind, and Tijl Verhoelst
Atmos. Chem. Phys., 22, 10319–10351, https://doi.org/10.5194/acp-22-10319-2022, https://doi.org/10.5194/acp-22-10319-2022, 2022
Short summary
Short summary
Using the COVID-19 lockdown periods as an example, we show how Sentinel-5P/TROPOMI trace gas data (NO2, SO2, CO, HCHO and CHOCHO) can be used to understand impacts on air quality for regions and cities around the globe. We also provide information for both experienced and inexperienced users about how we created the data using state-of-the-art algorithms, where to get the data, methods taking meteorological and seasonal variability into consideration, and insights for future studies.
Zhenqi Luo, Yuzhong Zhang, Wei Chen, Martin Van Damme, Pierre-François Coheur, and Lieven Clarisse
Atmos. Chem. Phys., 22, 10375–10388, https://doi.org/10.5194/acp-22-10375-2022, https://doi.org/10.5194/acp-22-10375-2022, 2022
Short summary
Short summary
We quantify global ammonia (NH3) emissions over the period from 2008 to 2018 using an improved fast top-down method that incorporates Infrared Atmospheric
Sounding Interferometer (IASI) satellite observations and GEOS-Chem atmospheric chemical simulations. The top-down analysis finds a global total NH3 emission that is 30 % higher than the bottom-up estimate, largely reconciling a large discrepancy of more than a factor of 2 found in previous top-down studies using the same satellite data.
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
Short summary
Short summary
We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Daniel J. Varon, Daniel J. Jacob, Melissa Sulprizio, Lucas A. Estrada, William B. Downs, Lu Shen, Sarah E. Hancock, Hannah Nesser, Zhen Qu, Elise Penn, Zichong Chen, Xiao Lu, Alba Lorente, Ashutosh Tewari, and Cynthia A. Randles
Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022, https://doi.org/10.5194/gmd-15-5787-2022, 2022
Short summary
Short summary
Reducing atmospheric methane emissions is critical to slow near-term climate change. Globally surveying satellite instruments like the TROPOspheric Monitoring Instrument (TROPOMI) have unique capabilities for monitoring atmospheric methane around the world. Here we present a user-friendly cloud-computing tool that enables researchers and stakeholders to quantify methane emissions across user-selected regions of interest using TROPOMI satellite observations.
Jonas Hachmeister, Oliver Schneising, Michael Buchwitz, Alba Lorente, Tobias Borsdorff, John P. Burrows, Justus Notholt, and Matthias Buschmann
Atmos. Meas. Tech., 15, 4063–4074, https://doi.org/10.5194/amt-15-4063-2022, https://doi.org/10.5194/amt-15-4063-2022, 2022
Short summary
Short summary
Sentinel-5P trace gas retrievals rely on elevation data in their calculations. Outdated or inaccurate data can lead to significant errors in e.g. dry-air mole fractions of methane (XCH4). We show that the use of inadequate elevation data leads to strong XCH4 anomalies in Greenland. Similar problems can be expected for other regions with inaccurate elevation data. However, we expect these to be more localized. We show that updating elevation data used in the retrieval solves this issue.
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
Short summary
Short summary
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.
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Oliver Schneising, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Robert J. Parker, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Markus Rettinger, Coleen Roehl, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, and Thorsten Warneke
Atmos. Meas. Tech., 15, 3401–3437, https://doi.org/10.5194/amt-15-3401-2022, https://doi.org/10.5194/amt-15-3401-2022, 2022
Short summary
Short summary
We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products.
In addition to an increased number of XCO2 data, v3 also includes products for XCH4 (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN2O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.
Vigneshkumar Balamurugan, Jia Chen, Zhen Qu, Xiao Bi, and Frank N. Keutsch
Atmos. Chem. Phys., 22, 7105–7129, https://doi.org/10.5194/acp-22-7105-2022, https://doi.org/10.5194/acp-22-7105-2022, 2022
Short summary
Short summary
In this study, we investigated the response of secondary pollutants to changes in precursor emissions, focusing on the formation of secondary PM, during the COVID-19 lockdown period. We show that, due to the decrease in primary NOx emissions, atmospheric oxidizing capacity is increased. The nighttime increase in ozone, caused by less NO titration, results in higher NO3 radicals, which contribute significantly to the formation of PM nitrates. O3 should be limited in order to control PM pollution.
John R. Worden, Daniel H. Cusworth, Zhen Qu, Yi Yin, Yuzhong Zhang, A. Anthony Bloom, Shuang Ma, Brendan K. Byrne, Tia Scarpelli, Joannes D. Maasakkers, David Crisp, Riley Duren, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 6811–6841, https://doi.org/10.5194/acp-22-6811-2022, https://doi.org/10.5194/acp-22-6811-2022, 2022
Short summary
Short summary
This paper is intended to accomplish two goals: 1) describe a new algorithm by which remotely sensed measurements of methane or other tracers can be used to not just quantify methane fluxes, but also attribute these fluxes to specific sources and regions and characterize their uncertainties, and 2) use this new algorithm to provide methane emissions by sector and country in support of the global stock take.
Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
Short summary
Short summary
Space-borne greenhouse gas missions require ground-based validation networks capable of providing fiducial reference measurements. Here, considerable refinements of the calibration procedures for the COllaborative Carbon Column Observing Network (COCCON) are presented. Laboratory and solar side-by-side procedures for the characterization of the spectrometers have been refined and extended. Revised calibration factors for XCO2, XCO and XCH4 are provided, incorporating 47 new spectrometers.
Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Alba Lorente, Franziska Aemisegger, David Noone, Dean Henze, Rigel Kivi, and Jochen Landgraf
Atmos. Meas. Tech., 15, 2251–2275, https://doi.org/10.5194/amt-15-2251-2022, https://doi.org/10.5194/amt-15-2251-2022, 2022
Short summary
Short summary
This paper presents an extended H₂O/HDO total column dataset from short-wave infrared measurements by TROPOMI including cloudy and clear-sky scenes. Coverage is tremendously increased compared to previous TROPOMI HDO datasets. The new dataset is validated against recent ground-based FTIR measurements from TCCON and against aircraft measurements over the ocean. The use of the new dataset is demonstrated with a case study of a cold air outbreak in January 2020.
Tia R. Scarpelli, Daniel J. Jacob, Shayna Grossman, Xiao Lu, Zhen Qu, Melissa P. Sulprizio, Yuzhong Zhang, Frances Reuland, Deborah Gordon, and John R. Worden
Atmos. Chem. Phys., 22, 3235–3249, https://doi.org/10.5194/acp-22-3235-2022, https://doi.org/10.5194/acp-22-3235-2022, 2022
Short summary
Short summary
We present a spatially explicit version of the national inventories of oil, gas, and coal methane emissions as submitted by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. We then use atmospheric modeling to compare our inventory emissions to atmospheric methane observations with the goal of identifying potential under- and overestimates of oil–gas methane emissions in the national inventories.
Haiyue Tan, Lin Zhang, Xiao Lu, Yuanhong Zhao, Bo Yao, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 22, 1229–1249, https://doi.org/10.5194/acp-22-1229-2022, https://doi.org/10.5194/acp-22-1229-2022, 2022
Short summary
Short summary
Methane is the second most important anthropogenic greenhouse gas. Understanding methane emissions and concentration growth over China in the past decade is important to support its mitigation. This study analyzes the contributions of methane emissions from different regions and sources over the globe to methane changes over China in 2007–2018. Our results show strong international transport influences and emphasize the need of intensive methane measurements covering eastern China.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
Short summary
Short summary
We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Qiansi Tu, Frank Hase, Matthias Schneider, Omaira García, Thomas Blumenstock, Tobias Borsdorff, Matthias Frey, Farahnaz Khosrawi, Alba Lorente, Carlos Alberti, Juan J. Bustos, André Butz, Virgilio Carreño, Emilio Cuevas, Roger Curcoll, Christopher J. Diekmann, Darko Dubravica, Benjamin Ertl, Carme Estruch, Sergio Fabián León-Luis, Carlos Marrero, Josep-Anton Morgui, Ramón Ramos, Christian Scharun, Carsten Schneider, Eliezer Sepúlveda, Carlos Toledano, and Carlos Torres
Atmos. Chem. Phys., 22, 295–317, https://doi.org/10.5194/acp-22-295-2022, https://doi.org/10.5194/acp-22-295-2022, 2022
Short summary
Short summary
We use different methane ground- and space-based remote sensing data sets for investigating the emission strength of three waste disposal sites close to Madrid. We present a method that uses wind-assigned anomalies for deriving emission strengths from satellite data and estimate their uncertainty to 9–14 %. The emission strengths estimated from the remote sensing data sets are significantly larger than the values published in the official register.
Sabour Baray, Daniel J. Jacob, Joannes D. Maasakkers, Jian-Xiong Sheng, Melissa P. Sulprizio, Dylan B. A. Jones, A. Anthony Bloom, and Robert McLaren
Atmos. Chem. Phys., 21, 18101–18121, https://doi.org/10.5194/acp-21-18101-2021, https://doi.org/10.5194/acp-21-18101-2021, 2021
Short summary
Short summary
We use 2010–2015 surface and satellite observations to disentangle methane from anthropogenic and natural sources in Canada. Using a chemical transport model (GEOS-Chem), the mismatch between modelled and observed methane concentrations can be used to infer emissions according to Bayesian statistics. Compared to prior knowledge, we show higher anthropogenic emissions attributed to energy and/or agriculture in Western Canada and lower natural emissions from Boreal wetlands.
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
Short summary
Short summary
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.
Luis Guanter, Cédric Bacour, Andreas Schneider, Ilse Aben, Tim A. van Kempen, Fabienne Maignan, Christian Retscher, Philipp Köhler, Christian Frankenberg, Joanna Joiner, and Yongguang Zhang
Earth Syst. Sci. Data, 13, 5423–5440, https://doi.org/10.5194/essd-13-5423-2021, https://doi.org/10.5194/essd-13-5423-2021, 2021
Short summary
Short summary
Sun-induced chlorophyll fluorescence (SIF) is an electromagnetic signal emitted by plants in the red and far-red parts of the spectrum. It has a functional link to photosynthesis and can be measured by satellite instruments, which makes it an important variable for the remote monitoring of the photosynthetic activity of vegetation ecosystems around the world. In this contribution we present a SIF dataset derived from the new Sentinel-5P TROPOMI missions.
Mark F. Lunt, Alistair J. Manning, Grant Allen, Tim Arnold, Stéphane J.-B. Bauguitte, Hartmut Boesch, Anita L. Ganesan, Aoife Grant, Carole Helfter, Eiko Nemitz, Simon J. O'Doherty, Paul I. Palmer, Joseph R. Pitt, Chris Rennick, Daniel Say, Kieran M. Stanley, Ann R. Stavert, Dickon Young, and Matt Rigby
Atmos. Chem. Phys., 21, 16257–16276, https://doi.org/10.5194/acp-21-16257-2021, https://doi.org/10.5194/acp-21-16257-2021, 2021
Short summary
Short summary
We present an evaluation of the UK's methane emissions between 2013 and 2020 using a network of tall tower measurement sites. We find emissions that are consistent in both magnitude and trend with the UK's reported emissions, with a declining trend driven by a decrease in emissions from England. The impact of various components of the modelling set-up on these findings are explored through a number of sensitivity studies.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Zhen Qu, Daniel J. Jacob, Lu Shen, Xiao Lu, Yuzhong Zhang, Tia R. Scarpelli, Hannah Nesser, Melissa P. Sulprizio, Joannes D. Maasakkers, A. Anthony Bloom, John R. Worden, Robert J. Parker, and Alba L. Delgado
Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, https://doi.org/10.5194/acp-21-14159-2021, 2021
Short summary
Short summary
The recent launch of TROPOMI offers an unprecedented opportunity to quantify the methane budget from a top-down perspective. We use TROPOMI and the more mature GOSAT methane observations to estimate methane emissions and get consistent global budgets. However, TROPOMI shows biases over regions where surface albedo is small and provides less information for the coarse-resolution inversion due to the larger error correlations and spatial variations in the number of observations.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
Short summary
Short summary
The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Tia R. Scarpelli, Melissa P. Sulprizio, Yuzhong Zhang, and Chris H. Rycroft
Atmos. Meas. Tech., 14, 5521–5534, https://doi.org/10.5194/amt-14-5521-2021, https://doi.org/10.5194/amt-14-5521-2021, 2021
Short summary
Short summary
Analytical inversions of satellite observations of atmospheric composition can improve emissions estimates and quantify errors but are computationally expensive at high resolutions. We propose two methods to decrease this cost. The methods reproduce a high-resolution inversion at a quarter of the cost. The reduced-dimension method creates a multiscale grid. The reduced-rank method solves the inversion where information content is highest.
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
Short summary
Short summary
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.
Chris Wilson, Martyn P. Chipperfield, Manuel Gloor, Robert J. Parker, Hartmut Boesch, Joey McNorton, Luciana V. Gatti, John B. Miller, Luana S. Basso, and Sarah A. Monks
Atmos. Chem. Phys., 21, 10643–10669, https://doi.org/10.5194/acp-21-10643-2021, https://doi.org/10.5194/acp-21-10643-2021, 2021
Short summary
Short summary
Methane (CH4) is an important greenhouse gas emitted from wetlands like those found in the basin of the Amazon River. Using an atmospheric model and observations from GOSAT, we quantified CH4 emissions from Amazonia during the previous decade. We found that the largest emissions came from a region in the eastern basin and that emissions there were rising faster than in other areas of South America. This finding was supported by CH4 observations made on aircraft within the basin.
Zhe Jin, Xiangjun Tian, Rui Han, Yu Fu, Xin Li, Huiqin Mao, and Cuihong Chen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-210, https://doi.org/10.5194/essd-2021-210, 2021
Manuscript not accepted for further review
Short summary
Short summary
Here we present a global and regional resolved terrestrial ecosystem and ocean carbon flux dataset during 2015–2019. The dataset was generated using the Tan-Tracker inversion system by absorbing satellite CO2 observations. The posterior 5-year annual mean global net carbon emissions were 5.35 PgC yr−1; the terrestrial ecosystem and ocean sinks were −4.07 and −3.33 PgC yr−1, respectively. This dataset can help understand global and regional carbon cycle, and support climate policy formulation.
Ilya Stanevich, Dylan B. A. Jones, Kimberly Strong, Martin Keller, Daven K. Henze, Robert J. Parker, Hartmut Boesch, Debra Wunch, Justus Notholt, Christof Petri, Thorsten Warneke, Ralf Sussmann, Matthias Schneider, Frank Hase, Rigel Kivi, Nicholas M. Deutscher, Voltaire A. Velazco, Kaley A. Walker, and Feng Deng
Atmos. Chem. Phys., 21, 9545–9572, https://doi.org/10.5194/acp-21-9545-2021, https://doi.org/10.5194/acp-21-9545-2021, 2021
Short summary
Short summary
We explore the utility of a weak-constraint (WC) four-dimensional variational (4D-Var) data assimilation scheme for mitigating systematic errors in methane simulation in the GEOS-Chem model. We use data from the Greenhouse Gases Observing Satellite (GOSAT) and show that, compared to the traditional 4D-Var approach, the WC scheme improves the agreement between the model and independent observations. We find that the WC corrections to the model provide insight into the source of the errors.
Qingyang Xiao, Yixuan Zheng, Guannan Geng, Cuihong Chen, Xiaomeng Huang, Huizheng Che, Xiaoye Zhang, Kebin He, and Qiang Zhang
Atmos. Chem. Phys., 21, 9475–9496, https://doi.org/10.5194/acp-21-9475-2021, https://doi.org/10.5194/acp-21-9475-2021, 2021
Short summary
Short summary
We used both statistical methods and a chemical transport model to assess the contribution of meteorology and emissions to PM2.5 during 2000–2018. Both methods revealed that emissions dominated the long-term PM2.5 trend with notable meteorological effects ranged up to 37.9 % of regional annual average PM2.5. The meteorological contribution became more beneficial to PM2.5 control in southern China but more unfavorable in northern China during the studied period.
Jasdeep Singh Anand, Alessandro Anav, Marcello Vitale, Daniele Peano, Nadine Unger, Xu Yue, Robert J. Parker, and Hartmut Boesch
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-125, https://doi.org/10.5194/bg-2021-125, 2021
Publication in BG not foreseen
Short summary
Short summary
Ozone damages plants, which prevents them from absorbing CO2 from the atmosphere. This poses a potential threat to preventing dangerous climate change. In this work, satellite observations of forest cover, ozone, climate, and growing season are combined with an empirical model to estimate the carbon lost due to ozone exposure over Europe. The estimated carbon losses agree well with prior modelled estimates, showing for the first time that satellites can be used to better understand this effect.
Jérôme Barré, Ilse Aben, Anna Agustí-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Peter Dueben, Richard Engelen, Antje Inness, Alba Lorente, Joe McNorton, Vincent-Henri Peuch, Gabor Radnoti, and Roberto Ribas
Atmos. Chem. Phys., 21, 5117–5136, https://doi.org/10.5194/acp-21-5117-2021, https://doi.org/10.5194/acp-21-5117-2021, 2021
Short summary
Short summary
This study presents a new approach to the systematic global detection of anomalous local CH4 concentration anomalies caused by rapid changes in anthropogenic emission levels. The approach utilises both satellite measurements and model simulations, and applies novel data analysis techniques (such as filtering and classification) to automatically detect anomalous emissions from point sources and small areas, such as oil and gas drilling sites, pipelines and facility leaks.
Xiao Lu, Daniel J. Jacob, Yuzhong Zhang, Joannes D. Maasakkers, Melissa P. Sulprizio, Lu Shen, Zhen Qu, Tia R. Scarpelli, Hannah Nesser, Robert M. Yantosca, Jianxiong Sheng, Arlyn Andrews, Robert J. Parker, Hartmut Boesch, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, https://doi.org/10.5194/acp-21-4637-2021, 2021
Short summary
Short summary
We use an analytical solution to the Bayesian inverse problem to quantitatively compare and combine the information from satellite and in situ observations, and to estimate global methane budget and their trends over the 2010–2017 period. We find that satellite and in situ observations are to a large extent complementary in the inversion for estimating global methane budget, and reveal consistent corrections of regional anthropogenic and wetland methane emissions relative to the prior inventory.
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
Short summary
Short summary
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.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jianxiong Sheng, Yuzhong Zhang, Xiao Lu, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, and Robert J. Parker
Atmos. Chem. Phys., 21, 4339–4356, https://doi.org/10.5194/acp-21-4339-2021, https://doi.org/10.5194/acp-21-4339-2021, 2021
Short summary
Short summary
We use 2010–2015 GOSAT satellite observations of atmospheric methane over North America in a high-resolution inversion to estimate methane emissions. We find general consistency with the gridded EPA inventory but higher oil and gas production emissions, with oil production emissions twice as large as in the latest EPA Greenhouse Gas Inventory. We find lower wetland emissions than predicted by WetCHARTs and a small increasing trend in the eastern US, apparently related to unconventional oil/gas.
Michael Buchwitz, Maximilian Reuter, Stefan Noël, Klaus Bramstedt, Oliver Schneising, Michael Hilker, Blanca Fuentes Andrade, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Hartmut Boesch, Lianghai Wu, Jochen Landgraf, Ilse Aben, Christian Retscher, Christopher W. O'Dell, and David Crisp
Atmos. Meas. Tech., 14, 2141–2166, https://doi.org/10.5194/amt-14-2141-2021, https://doi.org/10.5194/amt-14-2141-2021, 2021
Short summary
Short summary
The COVID-19 pandemic resulted in reduced anthropogenic carbon dioxide (CO2) emissions during 2020 in large parts of the world. We have used a small ensemble of satellite retrievals of column-averaged CO2 (XCO2) to find out if a regional-scale reduction of atmospheric CO2 can be detected from space. We focus on East China and show that it is challenging to reliably detect and to accurately quantify the emission reduction, which only results in regional XCO2 reductions of about 0.1–0.2 ppm.
Yuzhong Zhang, Daniel J. Jacob, Xiao Lu, Joannes D. Maasakkers, Tia R. Scarpelli, Jian-Xiong Sheng, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Jinfeng Chang, A. Anthony Bloom, Shuang Ma, John Worden, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 21, 3643–3666, https://doi.org/10.5194/acp-21-3643-2021, https://doi.org/10.5194/acp-21-3643-2021, 2021
Short summary
Short summary
We use 2010–2018 satellite observations of atmospheric methane to interpret the factors controlling atmospheric methane and its accelerating increase during the period. The 2010–2018 increase in global methane emissions is driven by tropical and boreal wetlands and tropical livestock (South Asia, Africa, Brazil), with an insignificant positive trend in emissions from the fossil fuel sector. The peak methane growth rates in 2014–2015 are also contributed by low OH and high fire emissions.
Alba Lorente, Tobias Borsdorff, Andre Butz, Otto Hasekamp, Joost aan de Brugh, Andreas Schneider, Lianghai Wu, Frank Hase, Rigel Kivi, Debra Wunch, David F. Pollard, Kei Shiomi, Nicholas M. Deutscher, Voltaire A. Velazco, Coleen M. Roehl, Paul O. Wennberg, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, https://doi.org/10.5194/amt-14-665-2021, 2021
Short summary
Short summary
TROPOMI aboard Sentinel-5P satellite provides methane (CH4) measurements with exceptional temporal and spatial resolution. The study describes a series of improvements developed to retrieve CH4 from TROPOMI. The updated CH4 product features (among others) a more accurate a posteriori correction derived independently of any reference data. The validation of the improved data product shows good agreement with ground-based and satellite measurements, which highlights the quality of the TROPOMI CH4.
Sudhanshu Pandey, Sander Houweling, Alba Lorente, Tobias Borsdorff, Maria Tsivlidou, A. Anthony Bloom, Benjamin Poulter, Zhen Zhang, and Ilse Aben
Biogeosciences, 18, 557–572, https://doi.org/10.5194/bg-18-557-2021, https://doi.org/10.5194/bg-18-557-2021, 2021
Short summary
Short summary
We use atmospheric methane observations from the novel TROPOspheric Monitoring Instrument (TROPOMI; Sentinel-5p) to estimate methane emissions from South Sudan's wetlands. Our emission estimates are an order of magnitude larger than the estimate of process-based wetland models. We find that this underestimation by the models is likely due to their misrepresentation of the wetlands' inundation extent and temperature dependences.
Ivar R. van der Velde, Guido R. van der Werf, Sander Houweling, Henk J. Eskes, J. Pepijn Veefkind, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 21, 597–616, https://doi.org/10.5194/acp-21-597-2021, https://doi.org/10.5194/acp-21-597-2021, 2021
Short summary
Short summary
This paper compares the relative atmospheric enhancements of CO and NO2 measured by the space-based instrument TROPOMI over different fire-prone ecosystems around the world. We find distinct spatial and temporal patterns in the ΔNO2 / ΔCO ratio that correspond to regional differences in combustion efficiency. This joint analysis provides a better understanding of regional-scale combustion characteristics and can help the fire modeling community to improve existing global emission inventories.
Shaojie Song, Tao Ma, Yuzhong Zhang, Lu Shen, Pengfei Liu, Ke Li, Shixian Zhai, Haotian Zheng, Meng Gao, Jonathan M. Moch, Fengkui Duan, Kebin He, and Michael B. McElroy
Atmos. Chem. Phys., 21, 457–481, https://doi.org/10.5194/acp-21-457-2021, https://doi.org/10.5194/acp-21-457-2021, 2021
Short summary
Short summary
We simulate the atmospheric chemical processes of an important sulfur-containing organic aerosol species, which is produced by the reaction between sulfur dioxide and formaldehyde. We can predict its distribution on a global scale. We find it is particularly rich in East Asia. This aerosol species is more abundant in the colder season partly because of weaker sunlight.
Robert J. Parker, Alex Webb, Hartmut Boesch, Peter Somkuti, Rocio Barrio Guillo, Antonio Di Noia, Nikoleta Kalaitzi, Jasdeep S. Anand, Peter Bergamaschi, Frederic Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Coleen Roehl, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Thorsten Warneke, Paul O. Wennberg, and Debra Wunch
Earth Syst. Sci. Data, 12, 3383–3412, https://doi.org/10.5194/essd-12-3383-2020, https://doi.org/10.5194/essd-12-3383-2020, 2020
Short summary
Short summary
This work presents the latest release of the University of Leicester GOSAT methane data and acts as the definitive description of this dataset. We detail the processing, validation and evaluation involved in producing these data and highlight its many applications. With now over a decade of global atmospheric methane observations, this dataset has helped, and will continue to help, us better understand the global methane budget and investigate how it may respond to a future changing climate.
Robert J. Parker, Chris Wilson, A. Anthony Bloom, Edward Comyn-Platt, Garry Hayman, Joe McNorton, Hartmut Boesch, and Martyn P. Chipperfield
Biogeosciences, 17, 5669–5691, https://doi.org/10.5194/bg-17-5669-2020, https://doi.org/10.5194/bg-17-5669-2020, 2020
Short summary
Short summary
Wetlands contribute the largest uncertainty to the atmospheric methane budget. WetCHARTs is a simple, data-driven model that estimates wetland emissions using observations of precipitation and temperature. We perform the first detailed evaluation of WetCHARTs against satellite data and find it performs well in reproducing the observed wetland methane seasonal cycle for the majority of wetland regions. In regions where it performs poorly, we highlight incorrect wetland extent as a key reason.
Mingjie Xie, Zhenzhen Zhao, Amara L. Holder, Michael D. Hays, Xi Chen, Guofeng Shen, James J. Jetter, Wyatt M. Champion, and Qin'geng Wang
Atmos. Chem. Phys., 20, 14077–14090, https://doi.org/10.5194/acp-20-14077-2020, https://doi.org/10.5194/acp-20-14077-2020, 2020
Short summary
Short summary
This study investigated the composition, structures, and light absorption of N-containing aromatic compounds (NACs) in PM2.5 emitted from burning red oak and charcoal in a variety of cookstoves. The results suggest that the identified NACs might have substantial fractions remaining in the gas phase. In comparison to other sources, cookstove emissions from red oak or charcoal fuels did not exhibit unique NAC structural features but had distinct NAC composition.
Cited articles
Alexe, M., Bergamaschi, P., Segers, A., Detmers, R., Butz, A., Hasekamp, O., Guerlet, S., Parker, R., Boesch, H., Frankenberg, C., Scheepmaker, R. A., Dlugokencky, E., Sweeney, C., Wofsy, S. C., and Kort, E. A.: Inverse modelling of CH4 emissions for 2010–2011 using different satellite retrieval products from GOSAT and SCIAMACHY, Atmos. Chem. Phys., 15, 113–133, https://doi.org/10.5194/acp-15-113-2015, 2015.
Bloom, A. A., Bowman, K. W., Lee, M., Turner, A. J., Schroeder, R., Worden, J. R., Weidner, R., McDonald, K. C., and Jacob, D. J.: A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0), Geosci. Model Dev., 10, 2141–2156, https://doi.org/10.5194/gmd-10-2141-2017, 2017.
Brasseur, G. P. and Jacob, D. J.: Modeling of Atmospheric Chemistry,
Cambridge University Press, Cambridge, USA, https://doi.org/10.1017/9781316544754, 2017.
Butz, A., Guerlet, S., Hasekamp, O. P., Schepers, D., Galli, A., Aben, I.,
Frankenberg, C., Hartmann, J.-M., Tran, H., Kuze, A., Keppel-Aleks, G.,
Toon, G. C., Wunch, D., Wennberg, P. O., Deutscher, N. M., Griffith, D. W.
T., Macatangay, R., Messerschmidt, J., Notholt, J., and Warneke, T.: Toward
accurate CO2 and CH4 observations from GOSAT, Geophys. Res. Lett., 38,
L14812, https://doi.org/10.1029/2011GL047888, 2011.
Chen, Z., Jacob, D. J., Nesser, H., Sulprizio, M. P., Lorente, A., Varon, D. J., Lu, X., Shen, L., Qu, Z., Penn, E., and Yu, X.: Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations, Atmos. Chem. Phys., 22, 10809–10826, https://doi.org/10.5194/acp-22-10809-2022, 2022.
Cressot, C., Chevallier, F., Bousquet, P., Crevoisier, C., Dlugokencky, E. J., Fortems-Cheiney, A., Frankenberg, C., Parker, R., Pison, I., Scheepmaker, R. A., Montzka, S. A., Krummel, P. B., Steele, L. P., and Langenfelds, R. L.: On the consistency between global and regional methane emissions inferred from SCIAMACHY, TANSO-FTS, IASI and surface measurements, Atmos. Chem. Phys., 14, 577–592, https://doi.org/10.5194/acp-14-577-2014, 2014.
Deng, Z., Ciais, P., Tzompa-Sosa, Z. A., Saunois, M., Qiu, C., Tan, C., Sun, T., Ke, P., Cui, Y., Tanaka, K., Lin, X., Thompson, R. L., Tian, H., Yao, Y., Huang, Y., Lauerwald, R., Jain, A. K., Xu, X., Bastos, A., Sitch, S., Palmer, P. I., Lauvaux, T., d'Aspremont, A., Giron, C., Benoit, A., Poulter, B., Chang, J., Petrescu, A. M. R., Davis, S. J., Liu, Z., Grassi, G., Albergel, C., Tubiello, F. N., Perugini, L., Peters, W., and Chevallier, F.: Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions, Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, 2022.
Dlugokencky, E. J., Steele, L. P., Lang, P. M., and Masarie, K. A.: The
growth rate and distribution of atmospheric methane, J. Geophys. Res., 99,
17021–17043, https://doi.org/10.1029/94JD01245, 1994.
Dlugokencky, E. J., Nisbet, E. G., Fisher, R. E., and Lowry, D.: Global
atmospheric methane: budget, changes and dangers, Philos. T. Roy. Soc. A, 369, 2058–2072, https://doi.org/10.1098/rsta.2010.0341,
2011.
Dlugokencky, E. J., Crotwell, A. M., Mund, J. W., Crotwell, M. J., and
Thoning, K. W.: Atmospheric Methane Dry Air Mole Fractions from the NOAA GML
Carbon Cycle Cooperative Global Air Sampling Network, 1983–2020, Version:
2021-07-30 [data set], https://doi.org/10.15138/VNCZ-M766, 2021.
Feng, L., Palmer, P. I., Zhu, S., Parker, R. J., and Liu, Y.: Tropical
methane emissions explain large fraction of recent changes in global
atmospheric methane growth rate, Nat. Commun., 13, 1378,
https://doi.org/10.1038/s41467-022-28989-z, 2022.
Fletcher, S. E. M. and Schaefer, H.: Rising methane: A new climate
challenge, Science, 364, 932–933, https://doi.org/10.1126/science.aax1828,
2019.
Forster, P., Storelvmo, T., Armour, K., Collins, W., Dufresne, J.-L., Frame,
D., Lunt, D. J., Palmer, T. M. M. D., Watanabe, M., Wild, M., and Zhang, H.:
The Earth's Energy Budget, Climate Feedbacks, and Climate Sensitivity, in:
Climate Change 2021: The Physical Science Basis. Contribution of Working
Group I to the Sixth Assessment Report of the Intergovernmental Panel on
Climate Change, Cambridge University Press, Cambridge, UK, New York, NY, USA, https://doi.org/10.1017/9781009157896.009, 2021.
Frankenberg, C., Meirink, J. F., van Weele, M., Platt, U., and Wagner, T.:
Assessing Methane Emissions from Global Space-Borne Observations, Science,
308, 1010–1014, https://doi.org/10.1126/science.1106644, 2005.
Frankenberg, C., Meirink, J. F., Bergamaschi, P., Goede, A. P. H., Heimann,
M., Körner, S., Platt, U., van Weele, M., and Wagner, T.: Satellite
chartography of atmospheric methane from SCIAMACHY on board ENVISAT:
Analysis of the years 2003 and 2004, J. Geophys. Res., 111, D07303,
https://doi.org/10.1029/2005JD006235, 2006.
Fung, I. Y., John, J. G., Lerner, J., Matthews, E., Prather, M. J., Steele,
L. P., and Fraser, P. J.: Three dimensional model synthesis of the global
methane cycle, J. Geophys. Res., 96, 13033–13065,
https://doi.org/10.1029/91JD01247, 1991.
Ganesan, A. L., Rigby, M., Lunt, M. F., Parker, R. J., Boesch, H., Goulding,
N., Umezawa, T., Zahn, A., Chatterjee, A., Prinn, R. G., Tiwari, Y. K., van
der Schoot, M., and Krummel, P. B.: Atmospheric observations show accurate
reporting and little growth in India's methane emissions, Nat. Commun., 8,
836, https://doi.org/10.1038/s41467-017-00994-7, 2017.
Ganesan, A. L., Schwietzke, S., Poulter, B. I., Arnold, T., Lan, X., Rigby,
M. L., Vogel, F. R., Werf, G. R., Janssens-Maenhout, G., Boesch, H., Pandey,
S., Manning, A. J., Jackson, R. B., Nisbet, E. G., and Manning, M. R.:
Advancing Scientific Understanding of the Global Methane Budget in Support
of the Paris Agreement, Global Biogeochem. Cy., 33, 1475–1512,
https://doi.org/10.1029/2018GB006065, 2019.
Gao, J., Guan, C., Zhang, B., and Li, K.: Decreasing methane emissions from
China's coal mining with rebounded coal production, Environ. Res. Lett., 16,
124037, https://doi.org/10.1088/1748-9326/ac38d8, 2021.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs,
L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan,
K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A.,
da Silva, A. M., Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D.,
Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M.,
Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective
Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30,
5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Hansen, P. C.: Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, https://doi.org/10.1137/1.9780898719697, 1998.
Heald, C. L., Jacob, D. J., Jones, D. B. A., Palmer, P. I., Logan, J. A.,
Streets, D. G., Sachse, G. W., Gille, J., Hoffman, R. N., and Nehrkorn, T.:
Comparative inverse analysis of satellite (MOPITT) and aircraft (TRACE-P)
observations to estimate Asian sources of carbon monoxide, J. Geophys. Res.,
109, D23306, https://doi.org/10.1029/2004JD005185, 2004.
Hu, H., Hasekamp, O., Butz, A., Galli, A., Landgraf, J., Aan de Brugh, J., Borsdorff, T., Scheepmaker, R., and Aben, I.: The operational methane retrieval algorithm for TROPOMI, Atmos. Meas. Tech., 9, 5423–5440, https://doi.org/10.5194/amt-9-5423-2016, 2016.
Hu, H., Landgraf, J., Detmers, R., Borsdorff, T., Aan de Brugh, J., Aben,
I., Butz, A., and Hasekamp, O. P.: Toward Global Mapping of Methane With
TROPOMI: First Results and Intersatellite Comparison to GOSAT, Geophys. Res.
Lett., 45, 3682–3689, https://doi.org/10.1002/2018GL077259, 2018.
Jacob, D. J., Turner, A. J., Maasakkers, J. D., Sheng, J., Sun, K., Liu, X., Chance, K., Aben, I., McKeever, J., and Frankenberg, C.: Satellite observations of atmospheric methane and their value for quantifying methane emissions, Atmos. Chem. Phys., 16, 14371–14396, https://doi.org/10.5194/acp-16-14371-2016, 2016.
Jacob, D. J., Varon, D. J., Cusworth, D. H., Dennison, P. E., Frankenberg, C., Gautam, R., Guanter, L., Kelley, J., McKeever, J., Ott, L. E., Poulter, B., Qu, Z., Thorpe, A. K., Worden, J. R., and Duren, R. M.: Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane, Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, 2022.
Janssens-Maenhout, G., Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., Bergamaschi, P., Pagliari, V., Olivier, J. G. J., Peters, J. A. H. W., van Aardenne, J. A., Monni, S., Doering, U., Petrescu, A. M. R., Solazzo, E., and Oreggioni, G. D.: EDGAR v4.3.2 Global Atlas of the three major greenhouse gas emissions for the period 1970–2012, Earth Syst. Sci. Data, 11, 959–1002, https://doi.org/10.5194/essd-11-959-2019, 2019.
Kuze, A., Suto, H., Nakajima, M., and Hamazaki, T.: Thermal and near
infrared sensor for carbon observation Fourier-transform spectrometer on the
Greenhouse Gases Observing Satellite for greenhouse gases monitoring, Appl.
Optics, 48, 6716–6733, https://doi.org/10.1364/ao.48.006716, 2009.
Kuze, A., Suto, H., Shiomi, K., Kawakami, S., Tanaka, M., Ueda, Y., Deguchi, A., Yoshida, J., Yamamoto, Y., Kataoka, F., Taylor, T. E., and Buijs, H. L.: Update on GOSAT TANSO-FTS performance, operations, and data products after more than 6 years in space, Atmos. Meas. Tech., 9, 2445–2461, https://doi.org/10.5194/amt-9-2445-2016, 2016.
Lee, H., Han, S.-O., Ryoo, S.-B., Lee, J.-S., and Lee, G.-W.: The measurement of atmospheric CO2 at KMA GAW regional stations, its characteristics, and comparisons with other East Asian sites, Atmos. Chem. Phys., 19, 2149–2163, https://doi.org/10.5194/acp-19-2149-2019, 2019.
Liu, C., Sun, Y., Shan, C., Wang, W., Notholt, J., Palm, M., Yin, H., Tian,
Y., Gao, J., and Mao, H.: Long-Term Observations of Atmospheric Constituents
at the First Ground-Based High-Resolution Fourier-Transform Spectrometry
Observation Station in China, Engineering, 22, 201–214,
https://doi.org/10.1016/j.eng.2021.11.022, 2023.
Liu, G., Peng, S., Lin, X., Ciais, P., Li, X., Xi, Y., Lu, Z., Chang, J.,
Saunois, M., Wu, Y., Patra, P. K., Chandra, N., Zeng, H., and Piao, S.:
Recent Slowdown of Anthropogenic Methane Emissions in China Driven by
Stabilized Coal Production, Environ. Sci. Technol. Lett., 8, 739–746,
https://doi.org/10.1021/acs.estlett.1c00463, 2021.
Lorente, A., Borsdorff, T., Butz, A., Hasekamp, O., aan de Brugh, J., Schneider, A., Wu, L., Hase, F., Kivi, R., Wunch, D., Pollard, D. F., Shiomi, K., Deutscher, N. M., Velazco, V. A., Roehl, C. M., Wennberg, P. O., Warneke, T., and Landgraf, J.: Methane retrieved from TROPOMI: improvement of the data product and validation of the first 2 years of measurements, Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, 2021a.
Lorente, A., Borsdorff, T., aan de Brugh, J., Landgraf, J., and Hasekamp, O.: SRON S5P – RemoTeC scientific TROPOMI XCH4 [data set], https://ftp.sron.nl/open-access-data-2/TROPOMI/tropomi/ch4/14_14_Lorente_et_al_2020_AMTD/ (last access: 29 December 2021), 2021b.
Lorente, A., Borsdorff, T., Landgraf, J., and the SRON L2 team: SRON
RemoTeC-S5P scientific XCH4 data product Product User Guide,
https://personal.sron.nl/open-access-data-2/TROPOMI/tropomi/ch4/SRON_CH4_product_Jan2022.pdf (last access: 1 December 2022), 2022.
Lu, X., Jacob, D. J., Zhang, Y., Maasakkers, J. D., Sulprizio, M. P., Shen, L., Qu, Z., Scarpelli, T. R., Nesser, H., Yantosca, R. M., Sheng, J., Andrews, A., Parker, R. J., Boesch, H., Bloom, A. A., and Ma, S.: Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) observations, Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, 2021.
Maasakkers, J. D., Jacob, D. J., Sulprizio, M. P., Scarpelli, T. R., Nesser, H., Sheng, J.-X., Zhang, Y., Hersher, M., Bloom, A. A., Bowman, K. W., Worden, J. R., Janssens-Maenhout, G., and Parker, R. J.: Global distribution of methane emissions, emission trends, and OH concentrations and trends inferred from an inversion of GOSAT satellite data for 2010–2015, Atmos. Chem. Phys., 19, 7859–7881, https://doi.org/10.5194/acp-19-7859-2019, 2019.
McNorton, J., Bousserez, N., Agustí-Panareda, A., Balsamo, G., Cantarello, L., Engelen, R., Huijnen, V., Inness, A., Kipling, Z., Parrington, M., and Ribas, R.: Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion, Atmos. Chem. Phys., 22, 5961–5981, https://doi.org/10.5194/acp-22-5961-2022, 2022.
Miller, S. M., Michalak, A. M., Detmers, R., Hasekamp, O. P., Bruhwiler, L.,
and Schwietzke, S.: China's coal mine methane regulations have not curbed
growing emissions, Nat. Commun., 10, 303,
https://doi.org/10.1038/s41467-018-07891-7, 2019.
Monteil, G., Houweling, S., Butz, A., Guerlet, S., Schepers, D., Hasekamp,
O. P., Frankenberg, C., Scheepmaker, R. A., Aben, I., and Röckmann, T.:
Comparison of CH4 inversions based on 15 months of GOSAT and SCIAMACHY
observations, J. Geophys. Res.-Atmos., 118, 11807–11823,
https://doi.org/10.1002/2013JD019760, 2013.
Murguia-Flores, F., Arndt, S., Ganesan, A. L., Murray-Tortarolo, G., and Hornibrook, E. R. C.: Soil Methanotrophy Model (MeMo v1.0): a process-based model to quantify global uptake of atmospheric methane by soil, Geosci. Model Dev., 11, 2009–2032, https://doi.org/10.5194/gmd-11-2009-2018, 2018.
Nguyen, N. A. and Steinbacher, M.: Atmospheric CH4 at Pha Din by Viet Nam
Meteorological and Hydrological Administration, dataset published as
CH4_PDI_surface-insitu_VNMHA_data1 at WDCGG, ver. 2020-07-13-2137 [data set], https://doi.org/10.50849/WDCGG_0051-2035-1002-01-01-9999,
2021.
Nisbet, E. G., Manning, M. R., Dlugokencky, E. J., Fisher, R. E., Lowry, D.,
Michel, S. E., Myhre, C. L., Platt, S. M., Allen, G., Bousquet, P.,
Brownlow, R., Cain, M., France, J. L., Hermansen, O., Hossaini, R., Jones,
A. E., Levin, I., Manning, A. C., Myhre, G., Pyle, J. A., Vaughn, B. H.,
Warwick, N. J., and White, J. W. C.: Very Strong Atmospheric Methane Growth
in the 4 Years 2014–2017: Implications for the Paris Agreement, Global
Biogeochem. Cy., 33, 318–342, https://doi.org/10.1029/2018GB006009, 2019.
Pandey, S., Houweling, S., Krol, M., Aben, I., Chevallier, F., Dlugokencky, E. J., Gatti, L. V., Gloor, E., Miller, J. B., Detmers, R., Machida, T., and Röckmann, T.: Inverse modeling of GOSAT-retrieved ratios of total column CH4 and CO2 for 2009 and 2010, Atmos. Chem. Phys., 16, 5043–5062, https://doi.org/10.5194/acp-16-5043-2016, 2016.
Parker, R. J. and Boesch, H.: University of Leicester GOSAT Proxy XCH4 v9.0,
Centre for Environmental Data Analysis [data set],
https://doi.org/10.5285/18ef8247f52a4cb6a14013f8235cc1eb, 2020.
Parker, R. J., Boesch, H., Byckling, K., Webb, A. J., Palmer, P. I., Feng, L., Bergamaschi, P., Chevallier, F., Notholt, J., Deutscher, N., Warneke, T., Hase, F., Sussmann, R., Kawakami, S., Kivi, R., Griffith, D. W. T., and Velazco, V.: Assessing 5 years of GOSAT Proxy XCH4 data and associated uncertainties, Atmos. Meas. Tech., 8, 4785–4801, https://doi.org/10.5194/amt-8-4785-2015, 2015.
Parker, R. J., Webb, A., Boesch, H., Somkuti, P., Barrio Guillo, R., Di Noia, A., Kalaitzi, N., Anand, J. S., Bergamaschi, P., Chevallier, F., Palmer, P. I., Feng, L., Deutscher, N. M., Feist, D. G., Griffith, D. W. T., Hase, F., Kivi, R., Morino, I., Notholt, J., Oh, Y.-S., Ohyama, H., Petri, C., Pollard, D. F., Roehl, C., Sha, M. K., Shiomi, K., Strong, K., Sussmann, R., Té, Y., Velazco, V. A., Warneke, T., Wennberg, P. O., and Wunch, D.: A decade of GOSAT Proxy satellite CH4 observations, Earth Syst. Sci. Data, 12, 3383–3412, https://doi.org/10.5194/essd-12-3383-2020, 2020.
Qu, Z., Jacob, D. J., Shen, L., Lu, X., Zhang, Y., Scarpelli, T. R., Nesser, H., Sulprizio, M. P., Maasakkers, J. D., Bloom, A. A., Worden, J. R., Parker, R. J., and Delgado, A. L.: Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments, Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, 2021.
Rigby, M., Prinn, R. G., Fraser, P. J., Simmonds, P. G., Langenfelds, R. L.,
Huang, J., Cunnold, D. M., Steele, L. P., Krummel, P. B., Weiss, R. F.,
O'Doherty, S., Salameh, P. K., Wang, H. J., Harth, C. M., Mühle, J., and
Porter, L. W.: Renewed growth of atmospheric methane, Geophys. Res. Lett.,
35, L22805, https://doi.org/10.1029/2008GL036037, 2008.
Rodgers, C. D.: Inverse methods for atmospheric sounding: theory and practice, World Scientific, Singapore, ISBN 978-981-02-2740-1, 2000.
Saad, Y.: Iterative methods for sparse linear systems, 2nd ed., Society for Industrial and Applied Mathematics (SIAM), Philadelphia, https://doi.org/10.1137/1.9780898718003, 2003.
Scarpelli, T. R., Jacob, D. J., Maasakkers, J. D., Sulprizio, M. P., Sheng, J.-X., Rose, K., Romeo, L., Worden, J. R., and Janssens-Maenhout, G.: A global gridded (
Schepers, D., Guerlet, S., Butz, A., Landgraf, J., Frankenberg, C.,
Hasekamp, O., Blavier, J.-F., Deutscher, N. M., Griffith, D. W. T., Hase,
F., Kyro, E., Morino, I., Sherlock, V., Sussmann, R., and Aben, I.: Methane
retrievals from Greenhouse Gases Observing Satellite (GOSAT) shortwave
infrared measurements: Performance comparison of proxy and physics retrieval
algorithms, J. Geophys. Res.-Atmos., 117, D10307,
https://doi.org/10.1029/2012JD017549, 2012.
Schneising, O., Buchwitz, M., Reuter, M., Bovensmann, H., Burrows, J. P., Borsdorff, T., Deutscher, N. M., Feist, D. G., Griffith, D. W. T., Hase, F., Hermans, C., Iraci, L. T., Kivi, R., Landgraf, J., Morino, I., Notholt, J., Petri, C., Pollard, D. F., Roche, S., Shiomi, K., Strong, K., Sussmann, R., Velazco, V. A., Warneke, T., and Wunch, D.: A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor, Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, 2019.
Schuldt, K. N., Aalto, T., Andrews, A., Aoki, S., Arduini, J., Baier, B., Bergamaschi, P., Biermann, T., Biraud, S. C., Boenisch, H., Brailsford, G., Chen, H., Colomb, A., Conil, S., Cristofanelli, P., Cuevas, E., Daube, B., Davis, K., Mazière, M. D., Delmotte, M., Desai, A., DiGangi, J. P., Dlugokencky, E., Elkins, J. W., Emmenegger, L., Fischer, M. L., Gatti, L. V., Gehrlein, T., Gerbig, C., Gloor, E., Goto, D., Haszpra, L., Hatakka, J., Heimann, M., Heliasz, M., Hermanssen, O., Hintsa, E., Holst, J., Ivakhov, V., Jaffe, D., Joubert, W., Kang, H.-Y., Karion, A., Kazan, V., Keronen, P., Ko, M.-Y., Kominkova, K., Kort, E., Kozlova, E., Krummel, P., Kubistin, D., Labuschagne, C., Langenfelds, R., Laurent, O., Laurila, T., Lauvaux, T., Lee, J., Lee, H., Lee, C.-H., Lehner, I., Leppert, R., Leuenberger, M., Lindauer, M., Loh, Z., Lopez, M., Machida, T., Mammarella, I., Manca, G., Marek, M. V., Martin, M. Y., Matsueda, H., McKain, K., Miles, N., Miller, C. E., Miller, J. B., Moore, F., Morimoto, S., Munro, D., Myhre, C. L., Mölder, M., Müller-Williams, J., Nichol, S., Niwa, Y., O’Doherty, S., Obersteiner, F., Piacentino, S., Pichon, J. M., Pittman, J., Plass-Duelmer, C., Ramonet, M., Richardson, S., Rivas, P. P., Saito, K., Santoni, G., Sasakawa, M., Scheeren, B., Schuck, T., Schumacher, M., and Seifert, T.: Multi-laboratory compilation of atmospheric
methane data for the period 1983–2020; obspack_ch4_ 1_ GLOBALVIEWplus_v4.0_2021-10-14 [data set], https://doi.org/10.25925/20211001, 2021.
Sha, M. K., Langerock, B., Blavier, J.-F. L., Blumenstock, T., Borsdorff, T., Buschmann, M., Dehn, A., De Mazière, M., Deutscher, N. M., Feist, D. G., García, O. E., Griffith, D. W. T., Grutter, M., Hannigan, J. W., Hase, F., Heikkinen, P., Hermans, C., Iraci, L. T., Jeseck, P., Jones, N., Kivi, R., Kumps, N., Landgraf, J., Lorente, A., Mahieu, E., Makarova, M. V., Mellqvist, J., Metzger, J.-M., Morino, I., Nagahama, T., Notholt, J., Ohyama, H., Ortega, I., Palm, M., Petri, C., Pollard, D. F., Rettinger, M., Robinson, J., Roche, S., Roehl, C. M., Röhling, A. N., Rousogenous, C., Schneider, M., Shiomi, K., Smale, D., Stremme, W., Strong, K., Sussmann, R., Té, Y., Uchino, O., Velazco, V. A., Vigouroux, C., Vrekoussis, M., Wang, P., Warneke, T., Wizenberg, T., Wunch, D., Yamanouchi, S., Yang, Y., and Zhou, M.: Validation of methane and carbon monoxide from Sentinel-5 Precursor using TCCON and NDACC-IRWG stations, Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, 2021.
Shen, L., Zavala-Araiza, D., Gautam, R., Omara, M., Scarpelli, T. R., Sheng,
J., Sulprizio, M. P., Zhuang, J., Zhang, Y., Qu, Z., Lu, X., Hamburg, S. P.,
and Jacob, D. J.: Unravelling a large methane emission discrepancy in Mexico
using satellite observations, Remote Sens. Environ., 260, 112461,
https://doi.org/10.1016/j.rse.2021.112461, 2021.
Shen, L., Gautam, R., Omara, M., Zavala-Araiza, D., Maasakkers, J. D., Scarpelli, T. R., Lorente, A., Lyon, D., Sheng, J., Varon, D. J., Nesser, H., Qu, Z., Lu, X., Sulprizio, M. P., Hamburg, S. P., and Jacob, D. J.: Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins, Atmos. Chem. Phys., 22, 11203–11215, https://doi.org/10.5194/acp-22-11203-2022, 2022.
Sheng, J., Song, S., Zhang, Y., Prinn, R. G., and Janssens-Maenhout, G.:
Bottom-Up Estimates of Coal Mine Methane Emissions in China: A Gridded
Inventory, Emission Factors, and Trends, Environ. Sci. Tech. Lett., 6,
473–478, https://doi.org/10.1021/acs.estlett.9b00294, 2019.
Sheng, J., Tunnicliffe, R. L., Ganesan, A. L., Maasakkers, J. D., Shen, L.,
Prinn, R. G., Song, S., Zhang, Y., Scarpelli, T. R., Anthony Bloom, A.,
Rigby, M. L., Manning, A. J., Parker, R. J., Boesch, H., Lan, X., Zhang, B.,
Zhuang, M., and Lu, X.: Sustained methane emissions from China after 2012
despite declining coal production and rice-cultivated area, Environ. Res.
Lett., 16, 104018, https://doi.org/10.1088/1748-9326/ac24d1, 2021.
Stavert, A. R., Saunois, M., Canadell, J. G., Poulter, B., Jackson, R. B.,
Regnier, P., Lauerwald, R., Raymond, P. A., Allen, G. H., Patra, P. K.,
Bergamaschi, P., Bousquet, P., Chandra, N., Ciais, P., Gustafson, A.,
Ishizawa, M., Ito, A., Kleinen, T., Maksyutov, S., McNorton, J., Melton, J.
R., Müller, J., Niwa, Y., Peng, S., Riley, W. J., Segers, A., Tian, H.,
Tsuruta, A., Yin, Y., Zhang, Z., Zheng, B., and Zhuang, Q.: Regional trends
and drivers of the global methane budget, Glob. Change Biol., 28, 182–200,
https://doi.org/10.1111/gcb.15901, 2022.
Turner, A. J. and Jacob, D. J.: Balancing aggregation and smoothing errors in inverse models, Atmos. Chem. Phys., 15, 7039–7048, https://doi.org/10.5194/acp-15-7039-2015, 2015.
Turner, A. J., Jacob, D. J., Wecht, K. J., Maasakkers, J. D., Lundgren, E., Andrews, A. E., Biraud, S. C., Boesch, H., Bowman, K. W., Deutscher, N. M., Dubey, M. K., Griffith, D. W. T., Hase, F., Kuze, A., Notholt, J., Ohyama, H., Parker, R., Payne, V. H., Sussmann, R., Sweeney, C., Velazco, V. A., Warneke, T., Wennberg, P. O., and Wunch, D.: Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data, Atmos. Chem. Phys., 15, 7049–7069, https://doi.org/10.5194/acp-15-7049-2015, 2015.
UNFCCC: Greenhouse Gas
Inventory Data [data set], https://di.unfccc.int/detailed_data_ by_ party (last access: 30 May 2022), 2020.
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., de Vries, J.,
Otter, G., Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele,
M., Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann,
P., Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.:
TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global
observations of the atmospheric composition for climate, air quality and
ozone layer applications, Remote Sens. Environ., 120, 70–83,
https://doi.org/10.1016/j.rse.2011.09.027, 2012.
Wang, F., Maksyutov, S., Janardanan, R., Tsuruta, A., Ito, A., Morino, I.,
Yoshida, Y., Tohjima, Y., Kaiser, J. W., Janssens-Maenhout, G., Lan, X.,
Mammarella, I., Lavric, J. V., and Matsunaga, T.: Interannual variability on
methane emissions in monsoon Asia derived from GOSAT and surface
observations, Environ. Res. Lett., 16, 024040,
https://doi.org/10.1088/1748-9326/abd352, 2021.
Wecht, K. J., Jacob, D. J., Frankenberg, C., Jiang, Z., and Blake, D. R.:
Mapping of North American methane emissions with high spatial resolution by
inversion of SCIAMACHY satellite data, J. Geophys. Res.-Atmos., 119,
7741–7756, https://doi.org/10.1002/2014JD021551, 2014.
WMO: WMO Greenhouse Gas Bulletin – The State of Greenhouse Gases in the
Atmosphere Based on Global Observations through 2020, https://library.wmo.int/doc_num.php?explnum_id=10904 (last access: 6 July 2022), 2021.
Wunch, D., Wennberg, P. O., Toon, G. C., Connor, B. J., Fisher, B., Osterman, G. B., Frankenberg, C., Mandrake, L., O'Dell, C., Ahonen, P., Biraud, S. C., Castano, R., Cressie, N., Crisp, D., Deutscher, N. M., Eldering, A., Fisher, M. L., Griffith, D. W. T., Gunson, M., Heikkinen, P., Keppel-Aleks, G., Kyrö, E., Lindenmaier, R., Macatangay, R., Mendonca, J., Messerschmidt, J., Miller, C. E., Morino, I., Notholt, J., Oyafuso, F. A., Rettinger, M., Robinson, J., Roehl, C. M., Salawitch, R. J., Sherlock, V., Strong, K., Sussmann, R., Tanaka, T., Thompson, D. R., Uchino, O., Warneke, T., and Wofsy, S. C.: A method for evaluating bias in global measurements of CO2 total columns from space, Atmos. Chem. Phys., 11, 12317–12337, https://doi.org/10.5194/acp-11-12317-2011, 2011.
Yang, Y., Zhou, M., Langerock, B., Sha, M. K., Hermans, C., Wang, T., Ji, D., Vigouroux, C., Kumps, N., Wang, G., De Mazière, M., and Wang, P.: Ground-based FTIR CO2, CH4 and CO measurements at Xianghe, China, Royal Belgian Institute for Space Aeronomy [data set], https://doi.org/10.18758/71021049, 2019.
Yang, Y., Zhou, M., Langerock, B., Sha, M. K., Hermans, C., Wang, T., Ji, D., Vigouroux, C., Kumps, N., Wang, G., De Mazière, M., and Wang, P.: New ground-based Fourier-transform near-infrared solar absorption measurements of XCO2, XCH4 and XCO at Xianghe, China, Earth Syst. Sci. Data, 12, 1679–1696, https://doi.org/10.5194/essd-12-1679-2020, 2020.
Yin, Y., Chevallier, F., Ciais, P., Bousquet, P., Saunois, M., Zheng, B., Worden, J., Bloom, A. A., Parker, R. J., Jacob, D. J., Dlugokencky, E. J., and Frankenberg, C.: Accelerating methane growth rate from 2010 to 2017: leading contributions from the tropics and East Asia, Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, 2021.
Yokota, T., Yoshida, Y., Eguchi, N., Ota, Y., Tanaka, T., Watanabe, H., and
Maksyutov, S.: Global Concentrations of CO2 and CH4 Retrieved from GOSAT:
First Preliminary Results, Sola, 5, 160–163,
https://doi.org/10.2151/sola.2009-041, 2009.
Yoshida, Y., Kikuchi, N., Morino, I., Uchino, O., Oshchepkov, S., Bril, A., Saeki, T., Schutgens, N., Toon, G. C., Wunch, D., Roehl, C. M., Wennberg, P. O., Griffith, D. W. T., Deutscher, N. M., Warneke, T., Notholt, J., Robinson, J., Sherlock, V., Connor, B., Rettinger, M., Sussmann, R., Ahonen, P., Heikkinen, P., Kyrö, E., Mendonca, J., Strong, K., Hase, F., Dohe, S., and Yokota, T.: Improvement of the retrieval algorithm for GOSAT SWIR XCO2 and XCH4 and their validation using TCCON data, Atmos. Meas. Tech., 6, 1533–1547, https://doi.org/10.5194/amt-6-1533-2013, 2013.
Zhang, L., Jacob, D. J., Liu, X., Logan, J. A., Chance, K., Eldering, A., and Bojkov, B. R.: Intercomparison methods for satellite measurements of atmospheric composition: application to tropospheric ozone from TES and OMI, Atmos. Chem. Phys., 10, 4725–4739, https://doi.org/10.5194/acp-10-4725-2010, 2010.
Zhang, Y., Jacob, D. J., Maasakkers, J. D., Sulprizio, M. P., Sheng, J.-X., Gautam, R., and Worden, J.: Monitoring global tropospheric OH concentrations using satellite observations of atmospheric methane, Atmos. Chem. Phys., 18, 15959–15973, https://doi.org/10.5194/acp-18-15959-2018, 2018.
Zhang, Y., Gautam, R., Pandey, S., Omara, M., Maasakkers, J. D., Sadavarte,
P., Lyon, D. R., Nesser, H., Sulprizio, M. P., Varon, D. J., Zhang, R.,
Houweling, S., Zavala-Araiza, D., Alvarez, R. A., Lorente, A., Hamburg, S.
P., Aben, I., and Jacob, D. J.: Quantifying methane emissions from the
largest oil-producing basin in the United States from space, Sci. Adv., 6,
eaaz5120, https://doi.org/10.1126/sciadv.aaz5120, 2020.
Zhang, Y., Jacob, D. J., Lu, X., Maasakkers, J. D., Scarpelli, T. R., Sheng, J.-X., Shen, L., Qu, Z., Sulprizio, M. P., Chang, J., Bloom, A. A., Ma, S., Worden, J., Parker, R. J., and Boesch, H.: Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations, Atmos. Chem. Phys., 21, 3643–3666, https://doi.org/10.5194/acp-21-3643-2021, 2021.
Zhang, Y., Fang, S., Chen, J., Lin, Y., Chen, Y., Liang, R., Jiang, K.,
Parker, R. J., Boesch, H., Steinbacher, M., Sheng, J.-X., Lu, X., Song, S.,
and Peng, S.: Observed changes in China's methane emissions linked to policy
drivers, P. Natl. Acad. Sci. USA, 119, e2202742119,
https://doi.org/10.1073/pnas.2202742119, 2022.
Short summary
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.
We compare and evaluate East Asian methane emissions inferred from different satellite...
Altmetrics
Final-revised paper
Preprint