Articles | Volume 26, issue 8
https://doi.org/10.5194/acp-26-5477-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-26-5477-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Apr 2026
Research article |
| 22 Apr 2026
| 22 Apr 2026
Observational insights into atmospheric CO2 and CO at the urban canopy layer top in Metropolitan Shanghai, China
Shuang Fu
Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou, China
State Key Laboratory of Green Chemical Synthesis and Conversion, Zhejiang University of Technology, Hangzhou, China
Xuemei Qing
College of Environment, Zhejiang University of Technology, Hangzhou, China
Kunpeng Zang
Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou, China
College of Environment, Zhejiang University of Technology, Hangzhou, China
Yi Lin
Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou, China
College of Environment, Zhejiang University of Technology, Hangzhou, China
Shuo Liu
Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou, China
College of Environment, Zhejiang University of Technology, Hangzhou, China
Yuanyuan Chen
Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou, China
College of Environment, Zhejiang University of Technology, Hangzhou, China
Bingjiang Chen
Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou, China
College of Environment, Zhejiang University of Technology, Hangzhou, China
Wei Gao
Yangtze River Delta Center for Environmental Meteorology Prediction and Warning, Shanghai, China
Martin Steinbacher
Laboratory for Air Pollution/Environmental Technology, Empa, 8600 Dübendorf, Switzerland
Shuangxi Fang
CORRESPONDING AUTHOR
Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou, China
College of Environment, Zhejiang University of Technology, Hangzhou, China
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
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Liang Feng, Paul I. Palmer, Haolin Wang, Robert Parker, Hartmut Boesch, Sébastien C. Biraud, Łukasz Chmura, Emanuel Gloor, László Haszpra, Elena Kozlova, Euan G. Nisbet, Steffen M. Noe, Thomas Röckmann, Rodrigo Augusto Ferreira de Souza, and Martin Steinbacher
EGUsphere, https://doi.org/10.5194/egusphere-2026-2662, https://doi.org/10.5194/egusphere-2026-2662, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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This study examines the relative roles of emissions and oxidation in recent rapid methane growth. Using an ensemble Kalman filter, we quantify global methane sources and sinks for 2018–2024. Emission changes dominate the increase, except in 2020 when a COVID‑19‑related OH decline strongly affected sinks. Atmospheric photochemistry—including OH and CH₄ variability and temperature‑dependent oxidation—also significantly shapes the methane budget.
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.
Leonie Bernet, Benjamin T. Brem, Nicolas Bukowiecki, Stephan Henne, Jörg Klausen, Mathew Mutuku, David Njiru, Patricia Nying'uro, Christoph Zellweger, and Martin Steinbacher
Atmos. Chem. Phys., 26, 6741–6762, https://doi.org/10.5194/acp-26-6741-2026, https://doi.org/10.5194/acp-26-6741-2026, 2026
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Long-term atmospheric measurements are crucial to understanding climate change but remain scarce across Africa. We monitored atmospheric species at Mt. Kenya from 2020 to 2024. Our data reveal equatorial seasonal and daily variability and show that models miss local patterns. Emissions at Mt. Kenya mainly come from households, industry, and agriculture, though with large uncertainties. These findings stress the need for more ground stations to improve climate models and emission estimates.
Thomas Laemmel, Dylan Geissbühler, Stephan Henne, Ryo Fujita, Heather Graven, Christophe Espic, Matthias Bantle, Negar Haghipour, Franz Conen, Dominik Brunner, Martin Steinbacher, Giulia Zazzeri, Samuel Hammer, Markus Leuenberger, and Sönke Szidat
EGUsphere, https://doi.org/10.5194/egusphere-2026-265, https://doi.org/10.5194/egusphere-2026-265, 2026
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Carbon dioxide and methane are the two main anthropogenic greenhouse gases responsible for current climate change. Beside the measurement of their atmospheric concentration, the analysis of the abundance of their isotope carbon-14 (14C) gives hints about their origin, either biogenic or fossil. Here we present six years of atmospheric 14CH4 and 14CO2 measurements at a high-elevation alpine site in Switzerland (Jungfraujoch) and discuss the observed trends in both local and global views.
Bernard Grobety, Philippe Favreau, Juanita Rausch, David Jaramillo, Martin Steinbacher, and Christoph Neururer
Aerosol Research Discuss., https://doi.org/10.5194/ar-2026-6, https://doi.org/10.5194/ar-2026-6, 2026
Revised manuscript under review for AR
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The iberulite fall was, to our knowledge, the first reported in central Europe. Special was, that the fall was observed in-situ and that the meteorological conditions during the fall are well known. The meteorology, the particle size distribution inside the iberulites, and the presence of a Greenfield gap in the latter strongly corroborates below-cloud scavenging as probable formation mechanism.
Martine Collaud Coen, Benjamin Tobias Brem, Martin Gysel-Beer, Robin Modini, Stephan Henne, Martin Steinbacher, Davide Putero, Maria I. Gini, and Kostantinos Eleftheriadis
Atmos. Chem. Phys., 26, 1623–1645, https://doi.org/10.5194/acp-26-1623-2026, https://doi.org/10.5194/acp-26-1623-2026, 2026
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Saharan dust (SD) is transported over long distances by large-scale atmospheric circulation, reaching the Jungfraujoch high-altitude station 30 to 150 times per year. This study analyses the influence of instrument types on the SD detection using the single scattering albedo spectral dependence. This optical method is then compared to those based on size distribution and back-trajectories. The 23-year climatology of dust frequency and mass as well as the source sensitivity are also examined.
Shuo Liu, Zeping Jin, Ziyi Chen, Haolin Li, Zihan Fan, Shaohui Li, Haiwang Fu, Wei He, Kunpeng Zang, Shuangxi Fang, and Peng Yan
EGUsphere, https://doi.org/10.5194/egusphere-2025-5065, https://doi.org/10.5194/egusphere-2025-5065, 2025
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We studied how planting green manure between tea rows affects carbon dioxide release from tea fields. Mixing legume and grass species improved soil health, reduced emissions from tea rows, and stabilized carbon over time. Although inter-row areas released more carbon, overall emissions declined with continued intercropping. This shows that green manure can make tea farming more climate-friendly and sustainable.
Sina Voshtani, Dylan B. A. Jones, Debra Wunch, Drew C. Pendergrass, Paul O. Wennberg, David F. Pollard, Isamu Morino, Hirofumi Ohyama, Nicholas M. Deutscher, Frank Hase, Ralf Sussmann, Damien Weidmann, Rigel Kivi, Omaira García, Yao Té, Jack Chen, Kerry Anderson, Robin Stevens, Shobha Kondragunta, Aihua Zhu, Douglas Worthy, Senen Racki, Kathryn McKain, Maria V. Makarova, Nicholas Jones, Emmanuel Mahieu, Andrea Cadena-Caicedo, Paolo Cristofanelli, Casper Labuschagne, Elena Kozlova, Thomas Seitz, Martin Steinbacher, Reza Mahdi, and Isao Murata
Atmos. Chem. Phys., 25, 15527–15565, https://doi.org/10.5194/acp-25-15527-2025, https://doi.org/10.5194/acp-25-15527-2025, 2025
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We assess the complementarity of the greater temporal coverage provided by ground-based remote sensing data with the spatial coverage of satellite observations when these data are used together to quantify CO emissions from extreme wildfires in 2023. Our results reveal that the commonly used biomass burning emission inventories significantly underestimate the fire emissions and emphasize the importance of the ground-based remote sensing data in reducing uncertainties in the estimated emissions.
Yuri Brugnara, Martin Steinbacher, Simone Baffelli, and Lukas Emmenegger
Atmos. Chem. Phys., 25, 14221–14236, https://doi.org/10.5194/acp-25-14221-2025, https://doi.org/10.5194/acp-25-14221-2025, 2025
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GAW-QC (Global Atmosphere Watch-Quality Control) is an interactive dashboard for the quality control of in-situ atmospheric composition measurements made at stations taking part in the Global Atmosphere Watch network. Even though it is mainly targeted at station operators who want to analyze recent, not yet published measurements, it allows anybody to verify the quality of already published measurements using various anomaly detection algorithms as well as visual comparisons.
Liang Feng, Paul I. Palmer, Luke Smallman, Jingfeng Xiao, Paolo Cristofanelli, Ove Hermansen, John Lee, Casper Labuschagne, Simonetta Montaguti, Steffen M. Noe, Stephen M. Platt, Xinrong Ren, Martin Steinbacher, and Irène Xueref-Remy
Atmos. Chem. Phys., 25, 13053–13076, https://doi.org/10.5194/acp-25-13053-2025, https://doi.org/10.5194/acp-25-13053-2025, 2025
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The year 2023 saw unexpectedly large global atmospheric CO2 growth. Satellite data reveal a role for increased tropical emissions. Larger emissions over eastern Brazil can be explained by warmer temperatures, which has led to exceptional drought, while hydrological changes play more of a role in emission increases elsewhere in the tropics. Broadly, we find that this situation continues into 2024.
Lubna Dada, Benjamin T. Brem, Lidia-Marta Amarandi-Netedu, Martine Collaud Coen, Nikolaos Evangeliou, Christoph Hueglin, Nora Nowak, Robin Modini, Martin Steinbacher, and Martin Gysel-Beer
Aerosol Research, 3, 315–336, https://doi.org/10.5194/ar-3-315-2025, https://doi.org/10.5194/ar-3-315-2025, 2025
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We investigated the sources of ultrafine particles (UFPs) in Payerne, Switzerland, highlighting the significant role of secondary processes in elevating UFP concentrations to levels comparable to urban areas. As the first study in rural midland Switzerland to analyze new particle formation events and secondary contributions, it offers key insights for air quality regulation and the role of agriculture in Switzerland and central Europe.
Davide Putero, Paolo Cristofanelli, Kai-Lan Chang, Gaëlle Dufour, Gregory Beachley, Cédric Couret, Peter Effertz, Daniel A. Jaffe, Dagmar Kubistin, Jason Lynch, Irina Petropavlovskikh, Melissa Puchalski, Timothy Sharac, Barkley C. Sive, Martin Steinbacher, Carlos Torres, and Owen R. Cooper
Atmos. Chem. Phys., 23, 15693–15709, https://doi.org/10.5194/acp-23-15693-2023, https://doi.org/10.5194/acp-23-15693-2023, 2023
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We investigated the impact of societal restriction measures during the COVID-19 pandemic on surface ozone at 41 high-elevation sites worldwide. Negative ozone anomalies were observed for spring and summer 2020 for all of the regions considered. In 2021, negative anomalies continued for Europe and partially for the eastern US, while western US sites showed positive anomalies due to wildfires. IASI satellite data and the Carbon Monitor supported emission reductions as a cause of the anomalies.
Paolo Cristofanelli, Cosimo Fratticioli, Lynn Hazan, Mali Chariot, Cedric Couret, Orestis Gazetas, Dagmar Kubistin, Antti Laitinen, Ari Leskinen, Tuomas Laurila, Matthias Lindauer, Giovanni Manca, Michel Ramonet, Pamela Trisolino, and Martin Steinbacher
Atmos. Meas. Tech., 16, 5977–5994, https://doi.org/10.5194/amt-16-5977-2023, https://doi.org/10.5194/amt-16-5977-2023, 2023
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We investigated the application of two automatic methods for detecting spikes due to local emissions in greenhouse gas (GHG) observations at a subset of sites from the ICOS Atmosphere network. We analysed the sensitivity to the spike frequency of using different methods and settings. We documented the impact of the de-spiking on different temporal aggregations (i.e. hourly, monthly and seasonal averages) of CO2, CH4 and CO 1 min time series.
Leonard Kirago, Örjan Gustafsson, Samuel Mwaniki Gaita, Sophie L. Haslett, Michael J. Gatari, Maria Elena Popa, Thomas Röckmann, Christoph Zellweger, Martin Steinbacher, Jörg Klausen, Christian Félix, David Njiru, and August Andersson
Atmos. Chem. Phys., 23, 14349–14357, https://doi.org/10.5194/acp-23-14349-2023, https://doi.org/10.5194/acp-23-14349-2023, 2023
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This study provides ground-observational evidence that supports earlier suggestions that savanna fires are the main emitters and modulators of carbon monoxide gas in Africa. Using isotope-based techniques, the study has shown that about two-thirds of this gas is emitted from savanna fires, while for urban areas, in this case Nairobi, primary sources approach 100 %. The latter has implications for air quality policy, suggesting primary emissions such as traffic should be targeted.
Jiaxin Li, Kunpeng Zang, Yi Lin, Yuanyuan Chen, Shuo Liu, Shanshan Qiu, Kai Jiang, Xuemei Qing, Haoyu Xiong, Haixiang Hong, Shuangxi Fang, Honghui Xu, and Yujun Jiang
Atmos. Meas. Tech., 16, 4757–4768, https://doi.org/10.5194/amt-16-4757-2023, https://doi.org/10.5194/amt-16-4757-2023, 2023
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Based on observed data of CO2 and CH4 and meteorological parameters over the Yellow Sea in November 2012 and June 2013, a data process and quality control method was optimized and established to filter the data influenced by multiple factors. Spatial and seasonal variations in CO2 and CH4 mixing ratios were mainly controlled by the East Asian Monsoon, while the influence of air–sea exchange was slight.
Peter Bergamaschi, Arjo Segers, Dominik Brunner, Jean-Matthieu Haussaire, Stephan Henne, Michel Ramonet, Tim Arnold, Tobias Biermann, Huilin Chen, Sebastien Conil, Marc Delmotte, Grant Forster, Arnoud Frumau, Dagmar Kubistin, Xin Lan, Markus Leuenberger, Matthias Lindauer, Morgan Lopez, Giovanni Manca, Jennifer Müller-Williams, Simon O'Doherty, Bert Scheeren, Martin Steinbacher, Pamela Trisolino, Gabriela Vítková, and Camille Yver Kwok
Atmos. Chem. Phys., 22, 13243–13268, https://doi.org/10.5194/acp-22-13243-2022, https://doi.org/10.5194/acp-22-13243-2022, 2022
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We present a novel high-resolution inverse modelling system, "FLEXVAR", and its application for the inverse modelling of European CH4 emissions in 2018. The new system combines a high spatial resolution of 7 km x 7 km with a variational data assimilation technique, which allows CH4 emissions to be optimized from individual model grid cells. The high resolution allows the observations to be better reproduced, while the derived emissions show overall good consistency with two existing models.
Simone M. Pieber, Béla Tuzson, Stephan Henne, Ute Karstens, Christoph Gerbig, Frank-Thomas Koch, Dominik Brunner, Martin Steinbacher, and Lukas Emmenegger
Atmos. Chem. Phys., 22, 10721–10749, https://doi.org/10.5194/acp-22-10721-2022, https://doi.org/10.5194/acp-22-10721-2022, 2022
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Understanding regional greenhouse gas emissions into the atmosphere is a prerequisite to mitigate climate change. In this study, we investigated the regional contributions of carbon dioxide (CO2) at the location of the high Alpine observatory Jungfraujoch (JFJ, Switzerland, 3580 m a.s.l.). To this purpose, we combined receptor-oriented atmospheric transport simulations for CO2 concentration in the period 2009–2017 with stable carbon isotope (δ13C–CO2) information.
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
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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.
Cyril Brunner, Benjamin T. Brem, Martine Collaud Coen, Franz Conen, Martin Steinbacher, Martin Gysel-Beer, and Zamin A. Kanji
Atmos. Chem. Phys., 22, 7557–7573, https://doi.org/10.5194/acp-22-7557-2022, https://doi.org/10.5194/acp-22-7557-2022, 2022
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Microscopic particles called ice-nucleating particles (INPs) are essential for ice crystals to form in clouds. INPs are a tiny proportion of atmospheric aerosol, and their abundance is poorly constrained. We study how the concentration of INPs changes diurnally and seasonally at a mountaintop station in central Europe. Unsurprisingly, a diurnal cycle is only found when considering air masses that have had lower-altitude ground contact. The highest INP concentrations occur in spring.
Makoto Saito, Tomohiro Shiraishi, Ryuichi Hirata, Yosuke Niwa, Kazuyuki Saito, Martin Steinbacher, Doug Worthy, and Tsuneo Matsunaga
Biogeosciences, 19, 2059–2078, https://doi.org/10.5194/bg-19-2059-2022, https://doi.org/10.5194/bg-19-2059-2022, 2022
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This study tested combinations of two sources of AGB data and two sources of LCC data and used the same burned area satellite data to estimate BB CO emissions. Our analysis showed large discrepancies in annual mean CO emissions and explicit differences in the simulated CO concentrations among the BB emissions estimates. This study has confirmed that BB emissions estimates are sensitive to the land surface information on which they are based.
Cyril Brunner, Benjamin T. Brem, Martine Collaud Coen, Franz Conen, Maxime Hervo, Stephan Henne, Martin Steinbacher, Martin Gysel-Beer, and Zamin A. Kanji
Atmos. Chem. Phys., 21, 18029–18053, https://doi.org/10.5194/acp-21-18029-2021, https://doi.org/10.5194/acp-21-18029-2021, 2021
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Special microscopic particles called ice-nucleating particles (INPs) are essential for ice crystals to form in the atmosphere. INPs are sparse and their atmospheric concentration and properties are not well understood. Mineral dust particles make up a significant fraction of INPs but how much remains unknown. Here, we address this knowledge gap by studying periods when mineral particles are present in large quantities at a mountaintop station in central Europe.
Larissa Lacher, Hans-Christian Clemen, Xiaoli Shen, Stephan Mertes, Martin Gysel-Beer, Alireza Moallemi, Martin Steinbacher, Stephan Henne, Harald Saathoff, Ottmar Möhler, Kristina Höhler, Thea Schiebel, Daniel Weber, Jann Schrod, Johannes Schneider, and Zamin A. Kanji
Atmos. Chem. Phys., 21, 16925–16953, https://doi.org/10.5194/acp-21-16925-2021, https://doi.org/10.5194/acp-21-16925-2021, 2021
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We investigate ice-nucleating particle properties at Jungfraujoch during the 2017 joint INUIT/CLACE field campaign, to improve the knowledge about those rare particles in a cloud-relevant environment. By quantifying ice-nucleating particles in parallel to single-particle mass spectrometry measurements, we find that mineral dust and aged sea spray particles are potential candidates for ice-nucleating particles. Our findings are supported by ice residual analysis and source region modeling.
Alex Resovsky, Michel Ramonet, Leonard Rivier, Jerome Tarniewicz, Philippe Ciais, Martin Steinbacher, Ivan Mammarella, Meelis Mölder, Michal Heliasz, Dagmar Kubistin, Matthias Lindauer, Jennifer Müller-Williams, Sebastien Conil, and Richard Engelen
Atmos. Meas. Tech., 14, 6119–6135, https://doi.org/10.5194/amt-14-6119-2021, https://doi.org/10.5194/amt-14-6119-2021, 2021
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We present a technical description of a statistical methodology for extracting synoptic- and seasonal-length anomalies from greenhouse gas time series. The definition of what represents an anomalous signal is somewhat subjective, which we touch on throughout the paper. We show, however, that the method performs reasonably well in extracting portions of time series influenced by significant North Atlantic Oscillation weather episodes and continent-wide terrestrial biospheric aberrations.
Cited articles
AGGI: The NOAA annual greenhouse gas index (AGGI), https://gml.noaa.gov/aggi/aggi.html (last access: 25 October 2025), 2024.
Allen, R. W., Gombojav, E., Barkhasragchaa, B., Byambaa, T., Lkhasuren, O., Amram, O., Takaro, T. K., and Janes, C. R.: An assessment of air pollution and its attributable mortality in Ulaanbaatar, Mongolia, Air Qual. Atmos. Hlth., 6, 137–150, https://doi.org/10.1007/s11869-011-0154-3, 2013.
Ammoura, L., Xueref-Remy, I., Vogel, F., Gros, V., Baudic, A., Bonsang, B., Delmotte, M., Té, Y., and Chevallier, F.: Exploiting stagnant conditions to derive robust emission ratio estimates for CO2, CO and volatile organic compounds in Paris, Atmos. Chem. Phys., 16, 15653–15664, https://doi.org/10.5194/acp-16-15653-2016, 2016.
Arnfield, A. J.: Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island, Int. J. Climatol., 23, 1–26, https://doi.org/10.1002/joc.859, 2003.
Bi, J., Zuidema, C., Clausen, D., Kirwa, K., Young Michael, T., Gassett Amanda, J., Seto Edmund, Y. W., Sampson Paul, D., Larson Timothy, V., Szpiro Adam, A., Sheppard, L., and Kaufman Joel, D.: Within-city variation in ambient carbon monoxide concentrations: Leveraging low-cost monitors in a spatiotemporal modeling framework, Environ. Health Persp., 130, 097008, https://pmc.ncbi.nlm.nih.gov/articles/PMC9518741/ (last access: 23 November 2025), 2022.
Bond, T. C., Streets, D. G., Yarber, K. F., Nelson, S. M., Woo, J.-H., and Klimont, Z.: A technology-based global inventory of black and organic carbon emissions from combustion, J. Geophys. Res.-Atmos., 109, https://doi.org/10.1029/2003JD003697, 2004.
Brunke, E. G., Labuschagne, C., Parker, B., Scheel, H. E., and Whittlestone, S.: Baseline air mass selection at Cape Point, South Africa: application of 222Rn and other filter criteria to CO2, Atmos. Environ., 38, 5693–5702, https://doi.org/10.1016/j.atmosenv.2004.04.024, 2004.
Carslaw, D. C.: The openair manual – Open-source tools for analysing air pollution data, Manual for version 2.6-2, King's College London, GitHub [code], https://github.com/davidcarslaw/openair (last access: 17 November 2021), 2019.
Carslaw, D. C. and Ropkins, K.: openair – An R package for air quality data analysis, Environ. Modell. Softw., 27–28, 52–61, https://doi.org/10.1016/j.envsoft.2011.09.008, 2012.
Che, K., Liu, Y., Cai, Z., Yang, D., Wang, H., Ji, D., Yang, Y., and Wang, P.: Characterization of regional combustion efficiency using ΔXCO: ΔXCO2 observed by a portable fourier-transform spectrometer at an urban site in Beijing, Adv. Atmos. Sci., 39, 1299–1315, https://doi.org/10.1007/s00376-022-1247-7, 2022.
Chen, Y., Cheng, J., Song, X., Liu, S., Sun, Y., Yu, D., and Fang, S.: Global-scale evaluation of XCO2 products from GOSAT, OCO-2 and carbontracker using direct comparison and triple collocation method, Remote Sens., 14, https://doi.org/10.3390/rs14225635, 2022.
Chen, Y., Lu, Y., Qi, B., Ma, Q., Zang, K., Lin, Y., Liu, S., Pan, F., Li, S., Guo, P., Chen, L., Lan, W., and Fang, S.: Atmospheric CO2 in the megacity Hangzhou, China: Urban-suburban differences, sources and impact factors, Sci. Total Environ., 926, https://doi.org/10.1016/j.scitotenv.2024.171635, 2024.
CMDC (China Meteorological Data Service Center): China Meteorological Data, China Meteorological Data Service Center [data set], https://doi.org/10.25504/FAIRsharing.52d9fa, 2024.
CNEMC (China National Environmental Monitoring Centre): China's air quality monitoring data, National Urban Air Quality Real-time Release Platform [data set], https://air.cnemc.cn:18007/ (last access: 1 August 2025), 2025.
CNCA (Carbon Neutral Cities Alliance): https://carbonneutralcities.org/about/ (last access: 25 October 2025), 2020.
Copernicus Climate Change Service: ERA5, the fifth generation ECMWF reanalysis for the global climate and weather: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Data Store [data set], https://doi.org/10.24381/cds.adbb2d47, 2025
Cosgrove, A. and Berkelhammer, M.: Downwind footprint of an urban heat island on air and lake temperatures, npj Clim. Atmos. Sci., 1, https://doi.org/10.1038/s41612-018-0055-3, 2018.
Crutzen, P.: A discussion of the chemistry of some minor constituents in the stratosphere and troposphere, Pure Appl. Geophys., 106, 1385–1399, https://doi.org/10.1007/BF00881092, 1973.
Denning, A.Zhang, N., Yi, C., Branson, M., Davis, K., Kleist, J., and Bakwin, P.: Evaluation of modeled atmospheric boundary layer depth at the WLEF tower, Agr. Forest Meteorol., 148, 206–215, https://doi.org/10.1016/j.agrformet.2007.08.012, 2008.
Djuricin, S., Xu, X., and Pataki, D. E.: The radiocarbon composition of tree rings as a tracer of local fossil fuel emissions in the Los Angeles basin: 1980–2008, J. Geophys. Res.-Atmos., 117, https://doi.org/10.1029/2011JD017284, 2012.
Ehhalt, D. H. and Rohrer, F.: The tropospheric cycle of H2: A critical review, Tellus B, 61, 500–535, https://doi.org/10.1111/j.1600-0889.2009.00416.x, 2009.
Fang, S., Luan, T., Zhang, G., Wu, Y., and Yu, D.: The determination of regional CO2 mole fractions at the Longfengshan WMO/GAW station: A comparison of four data filtering approaches, Atmos. Environ., 116, 36–43, https://doi.org/10.1016/j.atmosenv.2015.05.059, 2015a.
Fang, S., Zhou, L., Masarie, K. A., Xu, L., and Rella, C. W.: Study of atmospheric CH4 mole fractions at three WMO/GAW stations in China, J. Geophys. Res.-Atmos., 118, 4874–4886, https://doi.org/10.1002/jgrd.50284, 2013.
Fang, S., Tans, P. P., Steinbacher, M., Zhou, L., Luan, T., and Li, Z.: Observation of atmospheric CO2 and CO at Shangri-La station: results from the only regional station located at southwestern China, Tellus B, 68, https://doi.org/10.3402/tellusb.v68.28506, 2016.
Fang, S., Tans, P. P., Yao, B., Luan, T., Wu, Y., and Yu, D.: Study of atmospheric CO2 and CH4 at Longfengshan WMO/GAW regional station: The variations, trends, influence of local sources/sinks, and transport, Sci. China Earth Sci., 60, 1886–1895, https://doi.org/10.1007/s11430-016-9066-3, 2017.
Fang, S., Du, R., Qi, B., Ma, Q., Zhang, G., Chen, B., and Li, J.: Variation of carbon dioxide mole fraction at a typical urban area in the Yangtze River Delta, China, Atmos. Res., 265, https://doi.org/10.1016/j.atmosres.2021.105884, 2022.
Fang, S. X., Zhou, L. X., Tans, P. P., Ciais, P., Steinbacher, M., Xu, L., and Luan, T.: In situ measurement of atmospheric CO2 at the four WMO/GAW stations in China, Atmos. Chem. Phys., 14, 2541–2554, https://doi.org/10.5194/acp-14-2541-2014, 2014.
Fang, S. X., Tans, P. P., Steinbacher, M., Zhou, L. X., and Luan, T.: Comparison of the regional CO2 mole fraction filtering approaches at a WMO/GAW regional station in China, Atmos. Meas. Tech., 8, 5301–5313, https://doi.org/10.5194/amt-8-5301-2015, 2015b.
Fawole, O. G., Yusuf, N., Sunmonu, L. A., Obafaye, A., Audu, D. K., Onuorah, L., Olusegun, C. F., Deme, A., and Senghor, H.: Impacts of COVID-19 restrictions on regional and local air quality across selected West African cities, GeoHealth, 6, e2022GH000597, https://doi.org/10.1029/2022gh000597, 2022.
Forster, P., Ramaswamy, V., Artaxo, P., Berntsen, T., Betts, R., Fahey, D., Haywood, J., Lean, J., Lowe, D., Myhre, G., Nganga, J., Prinn, R., Raga, G., Michael, S., and Dorland, R.: Changes in Atmospheric Constituents and in Radiative Forcing, Chap. 2, in: The Physical Science Basis of Climate Change, edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, ISBN 978-0-521-88009-1, 2007.
Fu, J., Li, P., Lin, Y., Du, H., Liu, H., Zhu, W., and Ren, H.: Fight for carbon neutrality with state-of-the-art negative carbon emission technologies, Eco-Environment & Health, 1, 259–279, https://doi.org/10.1016/j.eehl.2022.11.005, 2022.
Fu, S. and Fang, S.: Shanghai Tower atmospheric CO2 and CO during 2021-2023, figshare [data set], https://doi.org/10.6084/m9.figshare.30918203, 2025.
GGMT: GAW Report No. 292: Twenty-first WMO/IAEA Meeting on Carbon Dioxide, Other Greenhouse Gases and Related Measurement Techniques (GGMT-2022), https://library.wmo.int/records/item/68925 (last access: 21 November 2025), 2024.
Han, S., Kondo, Y., Oshima, N., Takegawa, N., Miyazaki, Y., Hu, M., Lin, P., Deng, Z., Zhao, Y., Sugimoto, N., and Wu, Y.: Temporal variations of elemental carbon in Beijing, J. Geophys. Res.-Atmos., 114, https://doi.org/10.1029/2009JD012027, 2009.
Henry, C. R., Satran, D., Lindgren, B., Adkinson, C., Nicholson, C. I., and Henry, T. D.: Myocardial injury and long-term mortality following moderate to severe carbon monoxide poisoning, JAMA, 295, 398–402, https://doi.org/10.1001/jama.295.4.398, 2006.
Hirsch, R. and Gilroy, E.: Methods of fitting a straight line to data: Examples in water resources, Water Resour. Bull., 20, 705–711, https://doi.org/10.1111/j.1752-1688.1984.tb04753.x, 1984.
Huang, Y., Li, S., Zhu, Y., Liu, Y., Hong, Y., Chen, X., Deng, W., Xi, X., Lu, X., and Fan, Q.: Increasing sea-land breeze frequencies over coastal areas of China in the past five decades, Geophys. Res. Lett., 52, e2024GL112480, https://doi.org/10.1029/2024GL112480, 2025.
IPCC: Intergovernmental Panel on Climate Change. Climate Change 2021 – The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 675–714, https://doi.org/10.1017/9781009157896, 2023.
Kamal, A. T. M. M., Islam, M. S., Zaman, S. U., Miah, M. J., Ahmed, T., Hoque, S., and Salam, A.: Quantification and source apportionment of atmospheric trace gases over Dhaka, Bangladesh, J. Atmos. Chem., 81, 4, https://doi.org/10.1007/s10874-024-09457-y, 2024.
Kim, M.-K., Park, D., Kim, M., Heo, J., Park, S., and Chong, H.: A study on characteristic emission factors of exhaust gas from diesel locomotives, Int. J. Env. Res. Pub. He., 17, 3788, https://doi.org/10.3390/ijerph17113788, 2020.
Kondo, Y., Komazaki, Y., Miyazaki, Y., Moteki, N., Takegawa, N., Kodama, D., Deguchi, S., Nogami, M., Fukuda, M., Miyakawa, T., Morino, Y., Koike, M., Sakurai, H., and Ehara, K.: Temporal variations of elemental carbon in Tokyo, J. Geophys. Res.-Atmos., 111, https://doi.org/10.1029/2005JD006257, 2006.
Lelieveld, J., Gromov, S., Pozzer, A., and Taraborrelli, D.: Global tropospheric hydroxyl distribution, budget and reactivity, Atmos. Chem. Phys., 16, 12477–12493, https://doi.org/10.5194/acp-16-12477-2016, 2016.
Levin, I., Kromer, B., Schmidt, M., and Sartorius, H.: A novel approach for independent budgeting of fossil fuel CO2 over Europe by 14CO2 observations, Geophys. Res. Lett., 30, https://doi.org/10.1029/2003GL018477, 2003.
Li, Y., Tong, H., Zhuo, Y., Chen, C., and Xu, X.: Simultaneous removal of SO2 and trace SeO2 from flue gas: Effect of product layer on mass transfer, Environ. Sci. Technol., 40, 4306–4311, https://doi.org/10.1021/es052381s, 2006.
Li, Y., Deng, J., Mu, C., Xing, Z., and Du, K.: Vertical distribution of CO2 in the atmospheric boundary layer: Characteristics and impact of meteorological variables, Atmos. Environ., 91, 110–117, https://doi.org/10.1016/j.atmosenv.2014.03.067, 2014.
Li, Y., Ma, Z., Han, T., Quan, W., Wang, J., Zhou, H., He, D., and Dong, F.: Long-term declining in carbon monoxide (CO) at a rural site of Beijing during 2006–2018 implies the improved combustion efficiency and effective emission control, J. Environ. Sci., 115, 432–442, https://doi.org/10.1016/j.jes.2020.11.011, 2022.
Lin, J., Fang, S., He, R., Tang, Q., Qu, F., Wang, B., and Xu, W.: Monitoring ocean currents during the passage of Typhoon Muifa using optical-fiber distributed acoustic sensing, Nat. Commun., 15, 1111, https://doi.org/10.1038/s41467-024-45412-x, 2024.
Lin, Y., Zhang, Y., Xie, F., Fan, M., and Liu, X.: Substantial decreases of light absorption, concentrations and relative contributions of fossil fuel to light-absorbing carbonaceous aerosols attributed to the COVID-19 lockdown in east China, Environ. Pollut., 275, 116615, https://doi.org/10.1016/j.envpol.2021.116615, 2021.
Lin, Y., Li, S., Yu, Y., Lu, M., Chen, B., Chen, Y., Zang, K., Liu, S., Qi, B., and Fang, S.: A new regional background atmospheric station in the Yangtze River Delta region for carbon monoxide: Assessment of spatiotemporal characteristics and regional significance, Atmosphere, 16, https://doi.org/10.3390/atmos16010101, 2025.
Liu, L., Tans, P. P., Xia, L., Zhou, L., and Zhang, F.: Analysis of patterns in the concentrations of atmospheric greenhouse gases measured in two typical urban clusters in China, Atmos. Environ., 173, 343–354, https://doi.org/10.1016/j.atmosenv.2017.11.023, 2018.
Liu, P., Zhang, C., Mu, Y., Liu, C., Xue, C., Ye, C., Liu, J., Zhang, Y., and Zhang, H.: The possible contribution of the periodic emissions from farmers' activities in the North China Plain to atmospheric water-soluble ions in Beijing, Atmos. Chem. Phys., 16, 10097–10109, https://doi.org/10.5194/acp-16-10097-2016, 2016.
Liu, S., Fang, S., Liang, M., Ma, Q., and Feng, Z.: Study on CO data filtering approaches based on observations at two background stations in China, Sci. Total Environ., 691, 675–684, https://doi.org/10.1016/j.scitotenv.2019.07.162, 2019.
Liu, S., Chen, B., Fang, S., Zhang, C., Zang, K., He, W., Chen, Y., Lin, Y., Jin, Z., Chen, Z., Lan, W., and Xu, H.: Contrasting high-resolution vertical CO2 patterns: Insights from economically developed regions in Southeast China, J. Geophys. Res.-Atmos., 130, https://doi.org/10.1029/2024jd043181, 2025.
Meng, F., Hu, H., Sun, Y., Zhang, L., Hou, J., Zhang, Z., Pang, L., Cai, B., and Shan, Y.: Full-scope carbon dioxide emission dataset for Chinese cities in 2023, Sci. Data, 12, 1672, https://doi.org/10.1038/s41597-025-05949-y, 2025.
MOT (The Ministry of Transport of the People's Republic of China): Statistical Report on Transportation Industry Development 2022, MOT https://xxgk.mot.gov.cn/2020/jigou/zhghs/202205/t20220517_3655699.html (last access: 3 August 2025), 2022.
NOAA-ARL (Air Resources Laboratory): Global data assimilation system (GDAS) model one-degree archive, NOAA-ARL (Air Resources Laboratory), https://www.ready.noaa.gov/archives.php (last access: 1 August 2025), 2024.
Oke, T. R.: The distinction between canopy and boundary-layer urban heat islands, Atmosphere, 14, 268–277, https://doi.org/10.1080/00046973.1976.9648422, 1976.
Patel, A., Mallik, C., Chandra, N., Patra, P. K., and Steinbacher, M.: Revisiting regional and seasonal variations in decadal carbon monoxide variability: Global reversal of growth rate, Sci. Total Environ., 909, 168476, https://doi.org/10.1016/j.scitotenv.2023.168476, 2024.
Paul, S., Ghosh, S., Mathew, M., Devanand, A., Karmakar, S., and Niyogi, D.: Increased spatial variability and intensification of extreme monsoon rainfall due to urbanization, Sci. Rep., 8, 3918, https://doi.org/10.1038/s41598-018-22322-9, 2018.
Polissar, A. V., Hopke, P. K., Paatero, P., Kaufmann, Y. J., Hall, D. K., Bodhaine, B. A., Dutton, E. G., and Harris, J. M.: The aerosol at Barrow, Alaska: long-term trends and source locations, Atmos. Environ., 33, 2441–2458, https://doi.org/10.1016/S1352-2310(98)00423-3, 1999.
Popa, M. E., Vollmer, M. K., Jordan, A., Brand, W. A., Pathirana, S. L., Rothe, M., and Röckmann, T.: Vehicle emissions of greenhouse gases and related tracers from a tunnel study: CO : CO2, N2O : CO2, CH4 : CO2, O2 : CO2 ratios, and the stable isotopes 13C and 18O in CO2 and CO, Atmos. Chem. Phys., 14, 2105–2123, https://doi.org/10.5194/acp-14-2105-2014, 2014.
Pu, J., Xu, H., He, J., Fang, S., and Zhou, L.: Estimation of regional background concentration of CO2 at Lin'an Station in Yangtze River Delta, China, Atmos. Environ., 94, 402–408, https://doi.org/10.1016/j.atmosenv.2014.05.060, 2014.
Rogelj, J., McCollum, D. L., Reisinger, A., Meinshausen, M., and Riahi, K.: Probabilistic cost estimates for climate change mitigation, Nature, 493, 79–83, https://doi.org/10.1038/nature11787, 2013.
Rousseau, D.-D., Duzer, D., Etienne, J.-L., Cambon, G., Jolly, D., Ferrier, J., and Schevin, P.: Pollen record of rapidly changing air trajectories to the North Pole, J. Geophys. Res.: Atmos., 109, https://doi.org/10.1029/2003JD003985, 2004.
Ruckstuhl, A. F., Henne, S., Reimann, S., Steinbacher, M., Vollmer, M. K., O'Doherty, S., Buchmann, B., and Hueglin, C.: Robust extraction of baseline signal of atmospheric trace species using local regression, Atmos. Meas. Tech., 5, 2613–2624, https://doi.org/10.5194/amt-5-2613-2012, 2012.
Seiler, W.: Cycle of atmospheric CO, Tellus, 26, 116–135, https://doi.org/10.1111/j.2153-3490.1974.tb01958.x, 2010.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric chemistry and physics: From air pollution to climate change, 2nd edn., John Wiley & Sons, https://doi.org/10.1063/1.882420, 2016.
SHMS: Shanghai Municipal Human Resources and Social Security Bureau, http://rsj.sh.gov.cn/tgwyrsb_17088/20211220/t0035_1404512.html (last access: 11 January 2024), 2022.
Super, I., Denier van der Gon, H. A. C., Visschedijk, A. J. H., Moerman, M. M., Chen, H., van der Molen, M. K., and Peters, W.: Interpreting continuous in-situ observations of carbon dioxide and carbon monoxide in the urban port area of Rotterdam, Atmos. Pollut. Res., 8, 174–187, https://doi.org/10.1016/j.apr.2016.08.008, 2017.
Thoning, K. W., Tans, P. P., and Komhyr, W. D.: Atmospheric carbon dioxide at Mauna Loa Observatory: 2. Analysis of the NOAA GMCC data, 1974–1985, J. Geophys. Res.-Atmos., 94, 8549–8565, https://doi.org/10.1029/JD094iD06p08549, 1989.
Tian, X., Ren, B., Xie, P., Xu, J., Li, A., Hu, F., Zheng, J., Ren, H., Hu, Z., Pan, Y., Huang, X., Zhang, Z., Lv, Y., Tian, W., and Wang, Z.: The vertical distribution and potential sources of aerosols in the Yangtze River Delta region of China during open straw burning, Sci. Total Environ., 849, 157749, https://doi.org/10.1016/j.scitotenv.2022.157749, 2022.
Tohjima, Y., Kubo, M., Minejima, C., Mukai, H., Tanimoto, H., Ganshin, A., Maksyutov, S., Katsumata, K., Machida, T., and Kita, K.: Temporal changes in the emissions of CH4 and CO from China estimated from CH4
Tong, K., Fang, A., Li, Y., Shi, L., Wang, Y., Wang, S., and Ramaswami, A.: The collective contribution of Chinese cities to territorial and electricity-related CO2 emissions, J. Clean. Prod., 189, 910–921, https://doi.org/10.1016/j.jclepro.2018.04.037, 2018.
Tsutsumi, Y., Mori, K., Ikegami, M., Tashiro, T., and Tsuboi, K.: Long-term trends of greenhouse gases in regional and background events observed during 1998–2004 at Yonagunijima located to the east of the Asian continent, Atmos. Environ., 40, 5868–5879, https://doi.org/10.1016/j.atmosenv.2006.04.036, 2006.
Vásquez, M., Lara, W., Valle, J. I. D., and Sierra, C.: Reconstructing past fossil-fuel CO2 concentrations using tree rings and radiocarbon in the urban area of Medellín, Colombia, Environ. Res. Lett., 17, 055008, https://doi.org/10.1088/1748-9326/ac63d4, 2022.
Vega, M., Cespedes, L., Lombardo, F., Re, G., Garcia, N., Busnelli, A., Fedele, F. D., Lopez, M., Pomar, J., Salvati, A., and Piacentini, R.: Measurements and modelization of the Rosario City Heat Island, Argentina - Preliminary Results, IOP Conf. Ser.: Mater. Sci. Eng., 471, 092088, https://doi.org/10.1088/1757-899X/471/9/092088, 2019.
Wang, L., Li, D., Gao, Z., Sun, T., Guo, X., and Bou-Zeid, E.: Turbulent transport of momentum and scalars above an urban canopy, Bound.-Lay. Meteorol., 150, 485–511, https://doi.org/10.1007/s10546-013-9877-z, 2014.
Wang, L., Gu, X., Slater, L. J., Lai, Y., Zhang, X., Kong, D., Liu, J., and Li, J.: Indirect and direct impacts of typhoon In-Fa (2021) on heavy precipitation in inland and coastal areas of China: Synoptic-scale environments and return period analysis, Mon. Weather Rev., 151, 2377–2395, https://doi.org/10.1175/MWR-D-22-0241.1, 2023.
Wang, L., Xiong, Q., Wu, G., Gautam, A., Jiang, J., Liu, S., Zhao, W., and Guan, H.: Spatio-temporal variation characteristics of PM2.5 in the Beijing–Tianjin–Hebei Region, China, from 2013 to 2018, Int. J. Env. Res. Pub. He., 16, 4276, https://doi.org/10.3390/ijerph16214276, 2019.
Wang, S., Wang, Q., Zhu, S., Zhou, M., Qiao, L., Huang, D., Ma, Y., Lu, Y., Huang, C., Fu, Q., Duan, Y., and Yu, J. Z.: Hourly organic tracers-based source apportionment of PM2.5 before and during the Covid-19 lockdown in suburban Shanghai, China: Insights into regional transport influences and response to urban emission reductions, Atmos. Environ., 289, 119308, https://doi.org/10.1016/j.atmosenv.2022.119308, 2022.
Wang, Y., Munger, J. W., Xu, S., McElroy, M. B., Hao, J., Nielsen, C. P., and Ma, H.: CO2 and its correlation with CO at a rural site near Beijing: implications for combustion efficiency in China, Atmos. Chem. Phys., 10, 8881–8897, https://doi.org/10.5194/acp-10-8881-2010, 2010.
Wang, Z., Li, J., Wang, X., Pochanart, P., and Akimoto, H.: Modeling of regional high ozone episode observed at two mountain sites (Mt. Tai and Huang) in East China, J. Atmos. Chem., 55, 253–272, https://doi.org/10.1007/s10874-006-9038-6, 2006.
WDCGG (World Data Centre for Greenhouse Gases): WMO WDCGG Data Summary reports No. 49, https://gaw.kishou.go.jp/static/publications/summary/sum49/sum49.pdf (last access: 20 November 2025), 2025a.
WDCGG (World Data Centre for Greenhouse Gases): Greenhouse Gases Data, WDCGG [data set], https://gaw.kishou.go.jp/search (last access: 31 December 2025), 2025b.
Westerdahl, D., Wang, X., Pan, X., and Zhang, K. M.: Characterization of on-road vehicle emission factors and microenvironmental air quality in Beijing, China, Atmos. Environ., 43, 697–705, https://doi.org/10.1016/j.atmosenv.2008.09.042, 2009.
Winderlich, J., Gerbig, C., Kolle, O., and Heimann, M.: Inferences from CO2 and CH4 concentration profiles at the Zotino Tall Tower Observatory (ZOTTO) on regional summertime ecosystem fluxes, Biogeosciences, 11, 2055–2068, https://doi.org/10.5194/bg-11-2055-2014, 2014.
WMO: WMO Greenhouse Gas Bulletin, No. 21, The State of Greenhouse Gases in the Atmosphere Based on Global Observations through 2024, https://library.wmo.int/records/item/69654-no-21-16-october-2025 (last access: 27 October 2025), 2025.
Wu, D., Liu, J., Wennberg, P. O., Palmer, P. I., Nelson, R. R., Kiel, M., and Eldering, A.: Towards sector-based attribution using intra-city variations in satellite-based emission ratios between CO2 and CO, Atmos. Chem. Phys., 22, 14547–14570, https://doi.org/10.5194/acp-22-14547-2022, 2022.
Xia, L., Zhang, G., Liu, L., Li, B., Zhan, M., Kong, P., and Wang, H.: Atmospheric CO2 and CO at Jingdezhen station in central China: Understanding the regional transport and combustion efficiency, Atmos. Environ., 222, 117104, https://doi.org/10.1016/j.atmosenv.2019.117104, 2020.
Xiong, H., Fang, S., Zang, K., Lin, Y., Qiu, S., Hong, H., Li, J., Qing, X., and Jiang, K.: The utility model relates to a gas pretreatment device, CN215876659U, 2022-02-22, http://epub.cnipa.gov.cn/Dxb/PatentDetail (last access: 13 July 2025), 2022.
Yang, Y., Zhou, M., Wang, T., Yao, B., Han, P., Ji, D., Zhou, W., Sun, Y., Wang, G., and Wang, P.: Spatial and temporal variations of CO2 mole fractions observed at Beijing, Xianghe, and Xinglong in North China, Atmos. Chem. Phys., 21, 11741–11757, https://doi.org/10.5194/acp-21-11741-2021, 2021.
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.
Ye, C., Zhou, X., Zhang, Y., Wang, Y., Wang, J., Zhang, C., Woodward-Massey, R., Cantrell, C., Mauldin, R. L., Campos, T., Hornbrook, R. S., Ortega, J., Apel, E. C., Haggerty, J., Hall, S., Ullmann, K., Weinheimer, A., Stutz, J., Karl, T., Smith, J. N., Guenther, A., and Song, S.: Synthesizing evidence for the external cycling of NOx in high- to low-NOx atmospheres, Nat. Commun., 14, 7995, https://doi.org/10.1038/s41467-023-43866-z, 2023.
Ye, J., Zhang, Y., Yao, W., Liu, H., Lei, S., Zhang, Y., Zhang, J., Li, S., Lv, S., Wu, L., Tang, X., Sun, Y., Xin, J., Li, J., Wang, Z., Liu, L., Su, H., and Pan, X.: Significant shift of footprint patterns and pollutant source contributions: insights from observations at Shanghuang observatory, East China, Environ. Res. Lett., 19, https://doi.org/10.1088/1748-9326/ad8369, 2024.
Yuan, Y., Ries, L., Petermeier, H., Steinbacher, M., Gómez-Peláez, A. J., Leuenberger, M. C., Schumacher, M., Trickl, T., Couret, C., Meinhardt, F., and Menzel, A.: Adaptive selection of diurnal minimum variation: a statistical strategy to obtain representative atmospheric CO2 data and its application to European elevated mountain stations, Atmos. Meas. Tech., 11, 1501–1514, https://doi.org/10.5194/amt-11-1501-2018, 2018.
Zhang, F., Chen, Y., Tian, C., Lou, D., Li, J., Zhang, G., and Matthias, V.: Emission factors for gaseous and particulate pollutants from offshore diesel engine vessels in China, Atmos. Chem. Phys., 16, 6319–6334, https://doi.org/10.5194/acp-16-6319-2016, 2016.
Zhang, P., Wang, Y., Chen, T., Yu, Y., Ma, Q., Liu, C., Li, H., Chu, B., and He, H.: Insight into the Mechanism and Kinetics of the Heterogeneous Reaction between SO2 and NO2 on Diesel Black Carbon under Light Irradiation, Environ. Sci. Technol., 57, 17718–17726, https://doi.org/10.1021/acs.est.2c09674, 2023.
Zhang, W., Tong, S., Jia, C., Ge, M., Ji, D., Zhang, C., Liu, P., Zhao, X., Mu, Y., Hu, B., Wang, L., Tang, G., Li, X., Li, W., and Wang, Z.: Effect of different combustion processes on atmospheric nitrous acid formation mechanisms: a winter comparative observation in urban, suburban and rural areas of the North China Plain, Environ. Sci. Technol., 56, 4828–4837, https://doi.org/10.1021/acs.est.1c07784, 2022.
Zhao, D., Xin, J., Wang, W., Jia, D., Wang, Z., Xiao, H., Liu, C., Zhou, J., Tong, L., Ma, Y., Wen, T., Wu, F., and Wang, L.: Effects of the sea-land breeze on coastal ozone pollution in the Yangtze River Delta, China, Sci. Total Environ., 807, 150306, https://doi.org/10.1016/j.scitotenv.2021.150306, 2022.
Zhao, J., Chen, H., Qi, X., Chi, X., Jia, M., Jiang, F., Zhong, S., Zheng, B., and Ding, A.: Observed decade-long improvement of combustion efficiency in the Yangtze River Delta region in China, Environ. Res. Lett., 19, 074001, https://doi.org/10.1088/1748-9326/ad521e, 2024.
Zhao, X., Ding, J. M., and Suna, H. H.: Structural Design of Shanghai Tower for wind Loads, Procedia Engineer., 14, 1759–1767, https://doi.org/10.1016/j.proeng.2011.07.221, 2011.
Zheng, B., Chevallier, F., Yin, Y., Ciais, P., Fortems-Cheiney, A., Deeter, M. N., Parker, R. J., Wang, Y., Worden, H. M., and Zhao, Y.: Global atmospheric carbon monoxide budget 2000–2017 inferred from multi-species atmospheric inversions, Earth Syst. Sci. Data, 11, 1411–1436, https://doi.org/10.5194/essd-11-1411-2019, 2019.
Zhu, W., Kattel, S., Jiao, F., and Chen, J. G.: Shape-controlled CO2 electrochemical reduction on nanosized Pd hydride cubes and octahedra, Adv. Energy Mater., 9, https://doi.org/10.1002/aenm.201802840, 2019.
Short summary
Urban carbon dynamics are critical for climate action, yet remote background monitoring often misses key details. This study utilized the unique vantage point of the 632-m Shanghai Tower to investigate carbon dioxide and carbon monoxide dynamics directly above the urban core. Our research confirms such elevated observations can effectively track metropolitan-scale footprint, revealing fossil fuels as the dominant source (85%) of excess carbon dioxide and supporting targeted reduction measures.
Urban carbon dynamics are critical for climate action, yet remote background monitoring often...
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