Articles | Volume 18, issue 4
https://doi.org/10.5194/essd-18-2749-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-18-2749-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
21 Apr 2026
Data description article |
| 21 Apr 2026
| 21 Apr 2026
Deriving regional and point source nitrogen oxides emissions in China from TROPOMI using the directional derivative approach with nonlinear chemical lifetime fitting
Ling Chen
State Key laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
University of Chinese Academy of Sciences, Beijing 100049, China
Shanxi Center of Technology Innovation for Environmental Meteorology Forecast and Evaluation, Shanxi Institute of Meteorological Science, Taiyuan 030002, China
Zhaonan Cai
CORRESPONDING AUTHOR
State Key laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai, 200083, China
University of Chinese Academy of Sciences, Beijing 100049, China
Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, NY, USA
Research and Education in Energy, Environment and Water Institute, University at Buffalo, Buffalo, NY, USA
State Key laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
University of Chinese Academy of Sciences, Beijing 100049, China
Dongxu Yang
Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Mingming Li
Shanxi Center of Technology Innovation for Environmental Meteorology Forecast and Evaluation, Shanxi Institute of Meteorological Science, Taiyuan 030002, China
Lingyun Zhu
Shanxi Center of Technology Innovation for Environmental Meteorology Forecast and Evaluation, Shanxi Institute of Meteorological Science, Taiyuan 030002, China
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David J. Miller, Kang Sun, Jonathan E. Franklin, Nathan Leisso, Sébastien Roche, Bingkun Luo, Christopher Chan Miller, Sasha Ayvazov, Sean Crowell, Nick LoFaso, Tom Kampe, Peter Spuhler, Betsy Farris, Eleanor Walker, Tom Melendez, Ritesh Gautam, Xiong Liu, and Steven C. Wofsy
EGUsphere, https://doi.org/10.5194/egusphere-2026-2675, https://doi.org/10.5194/egusphere-2026-2675, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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With a focus on mitigating climate change, the MethaneSAT satellite mission aims to catalyze methane emission reductions. MethaneSAT has provided high-resolution emissions products across global oil and gas basins. We present novel calibration methods of MethaneSAT's instrumentation that demonstrate stable on-orbit performance compared with ground-based calibration. Our results are important for similar satellite missions focused on monitoring climate-relevant emissions.
You Yi, William J. Randel, Laura L. Pan, Yi Liu, Shuangxi Fang, Zhaonan Cai, Teresa Campos, and Benjamin Gaubert
EGUsphere, https://doi.org/10.5194/egusphere-2026-2644, https://doi.org/10.5194/egusphere-2026-2644, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Methane is a potent greenhouse gas, but how it reaches the upper atmosphere is not well known. Using satellite data, we show that the Asian summer monsoon plays a key role in transporting methane from the lower atmosphere to the upper atmosphere, where it affects both Earth's radiation and the amount of water vapor. Our findings reveal that a regional weather system can influence the global distribution of methane, helping scientists better predict future climate change.
Weiwei Pu, Jing Xu, Lingyun Zhu, Chao Liu, Liyan Zhou, Jian Dong, Shuangshuang Ge, and Zhiqiang Ma
Atmos. Chem. Phys., 26, 6133–6145, https://doi.org/10.5194/acp-26-6133-2026, https://doi.org/10.5194/acp-26-6133-2026, 2026
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This study presents a year of high-resolution NH3 measurements at a high-altitude mountain site in northern China. We found that NH3 levels at this elevation are remarkably similar to those at a regional background station, despite their vast difference in altitude and significant geographic distance. Our findings reveal that agricultural emissions from the North China Plain are efficiently transported to the lower free troposphere through complex mountain-plain circulations.
Ayesha Riaz, Kang Sun, Brian D. Baker, Brian Buma, Karen E. Cady-Pereira, Christopher Chan Miller, William C. Eddy III, Betsy M. Farris, Thomas U. Kampe, Eric A. Kort, Nathan P. Leisso, Robert Spurr, Emily R. Stuchiner, and Wendy H. Yang
EGUsphere, https://doi.org/10.5194/egusphere-2026-1482, https://doi.org/10.5194/egusphere-2026-1482, 2026
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N2O is a powerful greenhouse gas mainly released from agricultural soils, but its emissions are difficult to track as they vary strongly in space and time. We tested whether combining two kind of infrared measurements in one instrument could improve ability of airborne and satellite instruments to observe these emissions. We found that this combined approach improves sensitivity to near-surface emissions with low measurement error and could guide the design of future N2O dedicated missions.
Ethan Manninen, Apisada Chulakadabba, Maryann Sargent, Zhan Zhang, Harshil Kamdar, Jack Warren, Sébastien Roche, Christopher Chan Miller, Ethan Kyzivat, Joshua Benmergui, Jasna Pittman, Eleanor Walker, Jacob Bushey, Jenna Samra, Jacob Hawthorne, Bingkun Luo, Maya Nasr, Kang Sun, Jonathan Franklin, Xiong Liu, Jia Chen, and Steven Wofsy
EGUsphere, https://doi.org/10.5194/egusphere-2026-115, https://doi.org/10.5194/egusphere-2026-115, 2026
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In this work, my coauthors and I interpret methane emissions observed by remote sensing systems as plumes, or point sources. We model the probability that a general imaging spectrometer will detect a plume, and apply this framework to multiple remote sensing systems. We show how two recent systems- MethanAIR and MethaneSAT- provide enough sensitivity to facility scale point sources to effectively characterize most plume emissions in the Permian Basin.
Zhan Zhang, Maryann Sargent, Jack D. Warren, Apisada Chulakadabba, Marcus Russi, Sasha Ayvazov, Joshua Benmergui, Marvin Knapp, Ethan Kyzivat, Christopher C. Miller, Sébastien Roche, Bingkun Luo, David J. Miller, Maya Nasr, Kang Sun, James P. Williams, Katlyn MacKay, Mark Omara, Luis Guanter, Ritesh Gautam, Jonathan Franklin, Xiong Liu, and Steven C. Wofsy
EGUsphere, https://doi.org/10.5194/egusphere-2026-141, https://doi.org/10.5194/egusphere-2026-141, 2026
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Accurate plume identification from satellite imagery is important for measuring methane emissions, but weak signals often require time-consuming human inspection. We developed an automatic plume masking method that enhances plume patterns while reducing background noise based on wavelet transform image processing. The method finds more small emission sources with fewer false detections and works efficiently across different instruments, helping build a more complete picture of methane emissions.
Zitong Li, Kang Sun, Kaiyu Guan, Sheng Wang, Bin Peng, Lieven Clarisse, Martin Van Damme, Pierre-François Coheur, Karen Cady-Pereira, Mark W. Shephard, Mark Zondlo, and Daniel Moore
Atmos. Chem. Phys., 26, 703–721, https://doi.org/10.5194/acp-26-703-2026, https://doi.org/10.5194/acp-26-703-2026, 2026
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We estimate ammonia fluxes over the contiguous U.S. from 2008 to 2022 using a directional derivative approach applied to satellite observations from the Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS). The resulting flux estimates reveal pronounced seasonal and spatial patterns driven by agricultural activities and indicate substantial local deposition to surrounding vegetation, underscoring the need for improved monitoring and management strategies.
Sihong Zhu, Mengchu Tao, Zhaonan Cai, Yi Liu, Liang Feng, Pubu Sangmu, Zhongshui Yu, and Junji Cao
Atmos. Chem. Phys., 25, 9843–9857, https://doi.org/10.5194/acp-25-9843-2025, https://doi.org/10.5194/acp-25-9843-2025, 2025
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Methane (CH4) emissions can be transported into the upper troposphere (UT) via the Asian monsoon anticyclone (AMA), driving CH4 enhancements. Whether emissions or upward transport is the dominant factor remains debated. We analyzed UT CH4 variability with AMA dynamics, finding strong ties between CH4 distribution and the AMA's east–west oscillation. When centered near 80° E, vertical transport largely enhances CH4 anomalies, with circulation effects 1–2 times greater than those of emissions.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Christopher Chan Miller, Sébastien Roche, Jonas S. Wilzewski, Xiong Liu, Kelly Chance, Amir H. Souri, Eamon Conway, Bingkun Luo, Jenna Samra, Jacob Hawthorne, Kang Sun, Carly Staebell, Apisada Chulakadabba, Maryann Sargent, Joshua S. Benmergui, Jonathan E. Franklin, Bruce C. Daube, Yang Li, Joshua L. Laughner, Bianca C. Baier, Ritesh Gautam, Mark Omara, and Steven C. Wofsy
Atmos. Meas. Tech., 17, 5429–5454, https://doi.org/10.5194/amt-17-5429-2024, https://doi.org/10.5194/amt-17-5429-2024, 2024
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MethaneSAT is an upcoming satellite mission designed to monitor methane emissions from the oil and gas (O&G) industry globally. Here, we present observations from the first flight campaign of MethaneAIR, a MethaneSAT-like instrument mounted on an aircraft. MethaneAIR can map methane with high precision and accuracy over a typically sized oil and gas basin (~200 km2) in a single flight. This paper demonstrates the capability of the upcoming satellite to routinely track global O&G emissions.
Zhendong Lu, Jun Wang, Yi Wang, Daven K. Henze, Xi Chen, Tong Sha, and Kang Sun
Atmos. Chem. Phys., 24, 7793–7813, https://doi.org/10.5194/acp-24-7793-2024, https://doi.org/10.5194/acp-24-7793-2024, 2024
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In contrast with past work showing that the reduction of emissions was the dominant factor for the nationwide increase of surface O3 during the lockdown in China, this study finds that the variation in meteorology (temperature and other parameters) plays a more important role. This result is obtained through sensitivity simulations using a chemical transport model constrained by satellite (TROPOMI) data and calibrated with surface observations.
Xiaoyu Ren, Dongxu Yang, Yi Liu, Yong Wang, Ting Wang, Zhaonan Cai, Lu Yao, Tonghui Zhao, Jing Wang, and Zhe Jiang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-49, https://doi.org/10.5194/amt-2024-49, 2024
Publication in AMT not foreseen
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We aim to verify the performance of the low-cost CO2 sensors (LUCCN). The measurements show that accuracies of LUCCNs are higher than the medium accuracy standard. And LUCCNs are also sensitive to the changes of CO2 concentrations. These results prove that the LUCCN can measure CO2 concentrations effectively, which means that LUCCN is a powerful tool to achieve the CO2 monitoring network.
Eamon K. Conway, Amir H. Souri, Joshua Benmergui, Kang Sun, Xiong Liu, Carly Staebell, Christopher Chan Miller, Jonathan Franklin, Jenna Samra, Jonas Wilzewski, Sebastien Roche, Bingkun Luo, Apisada Chulakadabba, Maryann Sargent, Jacob Hohl, Bruce Daube, Iouli Gordon, Kelly Chance, and Steven Wofsy
Atmos. Meas. Tech., 17, 1347–1362, https://doi.org/10.5194/amt-17-1347-2024, https://doi.org/10.5194/amt-17-1347-2024, 2024
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The work presented here describes the processes required to convert raw sensor data for the MethaneAIR instrument to geometrically calibrated data. Each algorithm is described in detail. MethaneAIR is the airborne simulator for MethaneSAT, a new satellite under development by MethaneSAT LLC, a subsidiary of the EDF. MethaneSAT's goals are to precisely map over 80 % of the production sources of methane emissions from oil and gas fields across the globe to a high degree of accuracy.
Karen E. Cady-Pereira, Xuehui Guo, Rui Wang, April B. Leytem, Chase Calkins, Elizabeth Berry, Kang Sun, Markus Müller, Armin Wisthaler, Vivienne H. Payne, Mark W. Shephard, Mark A. Zondlo, and Valentin Kantchev
Atmos. Meas. Tech., 17, 15–36, https://doi.org/10.5194/amt-17-15-2024, https://doi.org/10.5194/amt-17-15-2024, 2024
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Ammonia is a significant precursor of PM2.5 particles and thus contributes to poor air quality in many regions. Furthermore, ammonia concentrations are rising due to the increase of large-scale, intensive agricultural activities. Here we evaluate satellite measurements of ammonia against aircraft and surface network data, and show that there are differences in magnitude, but the satellite data are spatially and temporally well correlated with the in situ data.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
Atmos. Meas. Tech., 16, 5771–5785, https://doi.org/10.5194/amt-16-5771-2023, https://doi.org/10.5194/amt-16-5771-2023, 2023
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We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
Rui Wang, Da Pan, Xuehui Guo, Kang Sun, Lieven Clarisse, Martin Van Damme, Pierre-François Coheur, Cathy Clerbaux, Melissa Puchalski, and Mark A. Zondlo
Atmos. Chem. Phys., 23, 13217–13234, https://doi.org/10.5194/acp-23-13217-2023, https://doi.org/10.5194/acp-23-13217-2023, 2023
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Ammonia (NH3) is a key precursor for fine particulate matter (PM2.5) and a primary form of reactive nitrogen, yet it has sparse ground measurements. We perform the first comprehensive comparison between ground observations and satellite retrievals in the US, demonstrating that satellite NH3 data can help fill spatial gaps in the current ground monitoring networks. Trend analyses using both datasets highlight increasing NH3 trends across the US, including the NH3 hotspots and urban areas.
Chantelle R. Lonsdale and Kang Sun
Atmos. Chem. Phys., 23, 8727–8748, https://doi.org/10.5194/acp-23-8727-2023, https://doi.org/10.5194/acp-23-8727-2023, 2023
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The COVID-19 pandemic, which was caused by the SARS-CoV-2 virus, emerged in 2019, and its still evolving variants have resulted in unprecedented shifts in human activities and anthropogenic emissions into the Earth's atmosphere. We present monthly nitrogen oxide emissions over three major continents from May 2018 to January 2023 to capture variations before and after the COVID-19 pandemic. We focus on a diverse collection of 54 cities to quantify the post-COVID-19 perturbations.
Huiqun Wang, Gonzalo González Abad, Chris Chan Miller, Hyeong-Ahn Kwon, Caroline R. Nowlan, Zolal Ayazpour, Heesung Chong, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Kang Sun, Robert Spurr, and Robert J. Hargreaves
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-66, https://doi.org/10.5194/amt-2023-66, 2023
Preprint withdrawn
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A pipeline for retrieving Total Column Water Vapor from satellite blue spectra is developed. New constraints are considered. Water-leaving radiance is important over the oceans. Results agree with reference datasets well under clear conditions. Due to high sensitivity to clouds, strict data filtering criteria are required. All-sky retrievals can be corrected using machine learning. GPS stations’ representation errors follow a power law relationship with grid resolutions.
Zolal Ayazpour, Shiqi Tao, Dan Li, Amy Jo Scarino, Ralph E. Kuehn, and Kang Sun
Atmos. Meas. Tech., 16, 563–580, https://doi.org/10.5194/amt-16-563-2023, https://doi.org/10.5194/amt-16-563-2023, 2023
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Accurate knowledge of the planetary boundary layer height (PBLH) is essential to study air pollution. However, PBLH observations are sparse in space and time, and PBLHs used in atmospheric models are often inaccurate. Using PBLH observations from the Aircraft Meteorological DAta Relay (AMDAR), we present a machine learning framework to produce a spatially complete PBLH product over the contiguous US that shows a better agreement with reference PBLH observations than commonly used PBLH products.
Kang Sun, Mahdi Yousefi, Christopher Chan Miller, Kelly Chance, Gonzalo González Abad, Iouli E. Gordon, Xiong Liu, Ewan O'Sullivan, Christopher E. Sioris, and Steven C. Wofsy
Atmos. Meas. Tech., 15, 3721–3745, https://doi.org/10.5194/amt-15-3721-2022, https://doi.org/10.5194/amt-15-3721-2022, 2022
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This study of upper atmospheric airglow from oxygen is motivated by the need to measure oxygen simultaneously with methane and CO2 in satellite remote sensing. We provide an accurate understanding of the spatial, temporal, and spectral distribution of airglow emissions, which will help in the satellite remote sensing of greenhouse gases and constraining the chemical and physical processes in the upper atmosphere.
Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
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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.
Lu Yao, Yi Liu, Dongxu Yang, Zhaonan Cai, Jing Wang, Chao Lin, Naimeng Lu, Daren Lyu, Longfei Tian, Maohua Wang, Zengshan Yin, Yuquan Zheng, and Sisi Wang
Atmos. Meas. Tech., 15, 2125–2137, https://doi.org/10.5194/amt-15-2125-2022, https://doi.org/10.5194/amt-15-2125-2022, 2022
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A physics-based SIF retrieval algorithm, IAPCAS/SIF, is introduced and applied to OCO-2 and TanSat measurements. The strong linear relationship between OCO-2 SIF retrieved by IAPCAS/SIF and the official product indicates the algorithm's reliability. The good consistency in the spatiotemporal patterns and magnitude of the OCO-2 and TanSat SIF products suggests that the combinative usage of multi-satellite products has potential and that such work would contribute to further research.
Amir H. Souri, Kelly Chance, Kang Sun, Xiong Liu, and Matthew S. Johnson
Atmos. Meas. Tech., 15, 41–59, https://doi.org/10.5194/amt-15-41-2022, https://doi.org/10.5194/amt-15-41-2022, 2022
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The central component of satellite and model validation is pointwise measurements. A point is an element of space, whereas satellite (model) pixels represent an averaged area. These two datasets are inherently different. We leveraged some geostatistical tools to transform discrete points to gridded data with quantified uncertainty, comparable to satellite footprint (and response functions). This in part alleviated some complications concerning point–pixel comparisons.
Kang Sun, Lingbo Li, Shruti Jagini, and Dan Li
Atmos. Chem. Phys., 21, 13311–13332, https://doi.org/10.5194/acp-21-13311-2021, https://doi.org/10.5194/acp-21-13311-2021, 2021
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We bridge the gap between satellite column observations and emissions by accounting for the dynamic lifetime of pollutants due to wind dispersion and the chemical lifetime due to chemical reactions. Applying it to the Po Valley air basin, we derive the monthly emissions of nitrogen oxides using satellite nitrogen dioxide observations. We further quantify the COVID-19-driven decline of emissions and estimate a 22 % decrease in nitrogen oxide emissions due to the pandemic in 2020.
Cited articles
Ayazpour, Z., Sun, K., Zhang, R., and Shen, H.: Evaluation of the Directional Derivative Approach for Timely and Accurate Satellite-Based Emission Estimation Using Chemical Transport Model Simulation of Nitrogen Oxides, J. Geophys. Res.-Atmos., 130, e2024JD042817, https://doi.org/10.1029/2024JD042817, 2025.
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Short summary
An appropriate representation of the NOx/NO2 ratio and NOx lifetime is essential for satellite-based NOx emissions estimation. We introduce a lightweight approach that applies variable NOx/NO2 ratios and piecewise fitting based on the directional derivative approach (DDA) to estimate regional and point-source NOx emissions. Our method directly captures nonlinear NOx chemistry and serves as an efficient alternative to both bottom-up inventories and computationally demanding top-down models.
An appropriate representation of the NOx/NO2 ratio and NOx lifetime is essential for...
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