Articles | Volume 26, issue 10
https://doi.org/10.5194/acp-26-7061-2026
© 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/acp-26-7061-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Measurement report: Temporal variability of vertical profiles of CO2 and CH4 over an urban environment
Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
Michał Gałkowski
Department of Biogeochemical Signals, Max Planck Institute for Biogeochemistry, Jena, Germany
Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
Piotr Sekula
Institute of Meteorology and Water Management, National Research Institute, Warsaw, Poland
Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
Łukasz Chmura
Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
Institute of Meteorology and Water Management, National Research Institute, Warsaw, Poland
Jakub Bartyzel
Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
Alina Jasek-Kamińska
Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
Institute of Meteorology and Water Management, National Research Institute, Warsaw, Poland
Alicja Skiba
Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
Jarosław Nęcki
Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
Paweł Jagoda
Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
Michał Kud
Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
Przemysław Wachniew
Faculty of Physics and Applied Computer Science, AGH University of Krakow, Krakow, Poland
Related authors
Anna K. Tobler, Alicja Skiba, Francesco Canonaco, Griša Močnik, Pragati Rai, Gang Chen, Jakub Bartyzel, Miroslaw Zimnoch, Katarzyna Styszko, Jaroslaw Nęcki, Markus Furger, Kazimierz Różański, Urs Baltensperger, Jay G. Slowik, and Andre S. H. Prevot
Atmos. Chem. Phys., 21, 14893–14906, https://doi.org/10.5194/acp-21-14893-2021, https://doi.org/10.5194/acp-21-14893-2021, 2021
Short summary
Short summary
Kraków is among the cities with the highest particulate matter levels within Europe. We conducted long-term and highly time-resolved measurements of the chemical composition of submicron particlulate matter (PM1). Combined with advanced source apportionment techniques, which allow for time-dependent factor profiles, our results elucidate that traffic and residential heating (biomass burning and coal combustion) as well as oxygenated organic aerosol are the key PM sources in Kraków.
Piotr Sekuła, Anita Bokwa, Jakub Bartyzel, Bogdan Bochenek, Łukasz Chmura, Michał Gałkowski, and Mirosław Zimnoch
Atmos. Chem. Phys., 21, 12113–12139, https://doi.org/10.5194/acp-21-12113-2021, https://doi.org/10.5194/acp-21-12113-2021, 2021
Short summary
Short summary
The wind shear generated on a local scale by the diversified relief’s impact can be a factor which significantly modifies the spatial pattern of PM10 concentration. The vertical profile of PM10 over a city located in a large valley during the events with high surface-level PM10 concentrations may show a sudden decrease with height not only due to the increase in wind speed, but also due to the change in wind direction alone. Vertical aerosanitary urban zones can be distinguished.
Noelia R. Benavente, Santiago Botía, Luciana V. Rizzo, Angel Vara-Vela, Paulo Artaxo, Hella van Asperen, Felipe Santos da Silva, Flavio A. F. D'Oliveira, Horst Fischer, Michał Gałkowski, Theo Glauch, Alice Henkes, David Ho, Cléo Q. Dias-Júnior, Amauri C. P. Junior, Julia Marshall, Linda Ort, Ben-Hur M. Portella, and Luiz A. T. Machado
EGUsphere, https://doi.org/10.5194/egusphere-2026-979, https://doi.org/10.5194/egusphere-2026-979, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
The Amazon Basin plays a vital role in regulating Earth's climate by absorbing and releasing carbon dioxide and methane. We studied how a high-resolution atmospheric transport model captures these gases, comparing it with measurements from towers and aircraft over the forest. Adjusting for forest carbon exchange improved carbon dioxide results, while methane levels were heavily dependent on emission estimates. Remaining errors were linked to winds and atmospheric mixing.
Thomas Röckmann, Malika Menoud, Jacoline van Es, Carina van der Veen, Hossein Maazallahi, Pawel Jagoda, Jaroslav M. Necki, Jakub Bartyzel, Piotr Korben, Sara Defratyka, Martina Schmidt, Marius Corbu, Sebastian Iancu, Andreea Calcan, Magdalena Ardelean, Sorin Ghemulet, Cristian Pop, Andrei Radovici, Alexandru Mereuta, Horatiu Stefanie, and Calin Baciu
Atmos. Chem. Phys., 26, 723–731, https://doi.org/10.5194/acp-26-723-2026, https://doi.org/10.5194/acp-26-723-2026, 2026
Short summary
Short summary
We report the isotopic composition of CH4 emitted from 48 installations in the gas production region of Transylvania, Romania which confirm the biogenic origin of the Transylvanian gas, produced by hydrogenotrophic CO2 reduction. This is similar to values reported previously from natural seeps and natural gas in a major city in the region. However, is more depleted in heavy isotopes than the oil-associated gas emitted in the Southern Romanian Plain, and gas leakages in the city of Bucharest.
Paul Waldmann, Max Eckl, Leon Knez, Klaus-Dirk Gottschaldt, Alina Fiehn, Christian Mallaun, Michał Gałkowski, Christoph Kiemle, Ronald Hutjes, Thomas Röckmann, Huilin Chen, and Anke Roiger
Atmos. Meas. Tech., 19, 185–210, https://doi.org/10.5194/amt-19-185-2026, https://doi.org/10.5194/amt-19-185-2026, 2026
Short summary
Short summary
Nitrous oxide and methane emissions from agriculture need to be reduced, therefore emissions must be understood to effectively mitigate them. This is the first approach to measure those emissions aircraft-based, to assess their magnitude and drivers. We identified emission hotspots and temporal changes in agricultural emissions in the Netherlands. Our approach is applicable to further greenhouse gas emitters, therefore it builds a step towards more comprehensive emission quantification.
Eric Förster, Heidi Huntrieser, Michael Lichtenstern, Falk Pätzold, Lutz Bretschneider, Andreas Schlerf, Sven Bollmann, Astrid Lampert, Jarosław Nęcki, Paweł Jagoda, Justyna Swolkień, Dominika Pasternak, Robert A. Field, and Anke Roiger
Atmos. Meas. Tech., 18, 7153–7176, https://doi.org/10.5194/amt-18-7153-2025, https://doi.org/10.5194/amt-18-7153-2025, 2025
Short summary
Short summary
We introduce a helicopter-borne mass balance approach, utilizing the HELiPOD platform, to accurately quantify methane (CH4) emissions from coal mining activities. The comparison of our top-down mass flux estimates (up to 3000 kg h−1) against those from bottom-up in-mine CH4 safety sensors revealed very good agreement. This approach also has a great potential in quantifying emission source strengths (down to 20 kg h−1) from a wide range of other CH4 emitters (e.g. landfills, oil & gas industry).
Dieu Anh Tran, Jordi Vilà-Guerau de Arellano, Ingrid T. Luijkx, Christoph Gerbig, Michał Gałkowski, Santiago Botía, Kim Faassen, and Sönke Zaehle
Atmos. Chem. Phys., 25, 16553–16588, https://doi.org/10.5194/acp-25-16553-2025, https://doi.org/10.5194/acp-25-16553-2025, 2025
Short summary
Short summary
Analysis of CH4 data (2010–2021) from ZOtino Tall Tower Observatory in Central Siberia shows an increase in the late summer diurnal amplitude, driven by nighttime emissions. These trends correlate with rising soil temperature and moisture during the late summer and snow depth of the preceding spring. Peaks in 2012 and 2019 emission link to wildfires activity. Findings suggest wetlands as key CH4 sources and underscore the need for ongoing high-resolution monitoring in this region.
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.
Michał Gałkowski, Julia Marshall, Blanca Fuentes Andrade, and Christoph Gerbig
Atmos. Chem. Phys., 25, 13831–13848, https://doi.org/10.5194/acp-25-13831-2025, https://doi.org/10.5194/acp-25-13831-2025, 2025
Short summary
Short summary
Observations of greenhouse gas emissions are needed to monitor the progress towards Paris Agreement goals. Remote sensing instruments have been used to estimate emissions from the strongest anthropogenic sources. Here, we study the impact of atmospheric turbulence on the estimation of CO₂ with a realistic atmospheric model, and we show that the formation of persistent plume structures causes uncertainty on the order of 10 % of total emission that cannot be avoided.
Theo Glauch, Julia Marshall, Christoph Gerbig, Santiago Botía, Michał Gałkowski, Sanam N. Vardag, and André Butz
Geosci. Model Dev., 18, 4713–4742, https://doi.org/10.5194/gmd-18-4713-2025, https://doi.org/10.5194/gmd-18-4713-2025, 2025
Short summary
Short summary
The Vegetation Photosynthesis and Respiration Model (VPRM) estimates carbon exchange between the atmosphere and biosphere by modeling gross primary production and respiration using satellite data and weather variables. Our new version, pyVPRM, supports diverse satellite products like Sentinel-2, MODIS, VIIRS, and new land cover maps, enabling high spatial and temporal resolution. This improves flux estimates, especially in complex landscapes, and ensures continuity as MODIS nears decommissioning.
Yosuke Niwa, Yasunori Tohjima, Yukio Terao, Tazu Saeki, Akihiko Ito, Taku Umezawa, Kyohei Yamada, Motoki Sasakawa, Toshinobu Machida, Shin-Ichiro Nakaoka, Hideki Nara, Hiroshi Tanimoto, Hitoshi Mukai, Yukio Yoshida, Shinji Morimoto, Shinya Takatsuji, Kazuhiro Tsuboi, Yousuke Sawa, Hidekazu Matsueda, Kentaro Ishijima, Ryo Fujita, Daisuke Goto, Xin Lan, Kenneth Schuldt, Michal Heliasz, Tobias Biermann, Lukasz Chmura, Jarsolaw Necki, Irène Xueref-Remy, and Damiano Sferlazzo
Atmos. Chem. Phys., 25, 6757–6785, https://doi.org/10.5194/acp-25-6757-2025, https://doi.org/10.5194/acp-25-6757-2025, 2025
Short summary
Short summary
This study estimated regional and sectoral emission contributions to the unprecedented surge of atmospheric methane for 2020–2022. The methane is the second most important greenhouse gas, and its emissions reduction is urgently required to mitigate global warming. Numerical modeling-based estimates with three different sets of atmospheric observations consistently suggested large contributions of biogenic emissions from South Asia and Southeast Asia to the surge of atmospheric methane.
Hector Navarro-Barboza, Jordi Rovira, Vincenzo Obiso, Andrea Pozzer, Marta Via, Andres Alastuey, Xavier Querol, Noemi Perez, Marjan Savadkoohi, Gang Chen, Jesus Yus-Díez, Matic Ivancic, Martin Rigler, Konstantinos Eleftheriadis, Stergios Vratolis, Olga Zografou, Maria Gini, Benjamin Chazeau, Nicolas Marchand, Andre S. H. Prevot, Kaspar Dallenbach, Mikael Ehn, Krista Luoma, Tuukka Petäjä, Anna Tobler, Jaroslaw Necki, Minna Aurela, Hilkka Timonen, Jarkko Niemi, Olivier Favez, Jean-Eudes Petit, Jean-Philippe Putaud, Christoph Hueglin, Nicolas Pascal, Aurélien Chauvigné, Sébastien Conil, Marco Pandolfi, and Oriol Jorba
Atmos. Chem. Phys., 25, 2667–2694, https://doi.org/10.5194/acp-25-2667-2025, https://doi.org/10.5194/acp-25-2667-2025, 2025
Short summary
Short summary
Brown carbon (BrC) absorbs ultraviolet (UV) and visible light, influencing climate. This study explores BrC's imaginary refractive index (k) using data from 12 European sites. Residential emissions are a major organic aerosol (OA) source in winter, while secondary organic aerosol (SOA) dominates in summer. Source-specific k values were derived, improving model accuracy. The findings highlight BrC's climate impact and emphasize source-specific constraints in atmospheric models.
Saqr Munassar, Christian Rödenbeck, Michał Gałkowski, Frank-Thomas Koch, Kai U. Totsche, Santiago Botía, and Christoph Gerbig
Atmos. Chem. Phys., 25, 639–656, https://doi.org/10.5194/acp-25-639-2025, https://doi.org/10.5194/acp-25-639-2025, 2025
Short summary
Short summary
CO2 mole fractions simulated over a global set of stations showed an overestimation of CO2 if the diurnal cycle is missing in biogenic fluxes. This leads to biases in the estimated fluxes derived from the regional-scale inversions. Interannual variability of estimated biogenic fluxes is also affected by the exclusion of the CO2 diurnal cycle. The findings point to the importance of including the diurnal variations of CO2 in the biogenic fluxes used as priors in global and regional inversions.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
Short summary
Short summary
Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Alina Fiehn, Maximilian Eckl, Julian Kostinek, Michał Gałkowski, Christoph Gerbig, Michael Rothe, Thomas Röckmann, Malika Menoud, Hossein Maazallahi, Martina Schmidt, Piotr Korbeń, Jarosław Neçki, Mila Stanisavljević, Justyna Swolkień, Andreas Fix, and Anke Roiger
Atmos. Chem. Phys., 23, 15749–15765, https://doi.org/10.5194/acp-23-15749-2023, https://doi.org/10.5194/acp-23-15749-2023, 2023
Short summary
Short summary
During the CoMet mission in the Upper Silesian Coal Basin (USCB) ground-based and airborne air samples were taken and analyzed for the isotopic composition of CH4 to derive the mean signature of the USCB and source signatures of individual coal mines. Using δ2H signatures, the biogenic emissions from the USCB account for 15 %–50 % of total emissions, which is underestimated in common emission inventories. This demonstrates the importance of δ2H-CH4 observations for methane source apportionment.
Xinxu Zhao, Jia Chen, Julia Marshall, Michal Gałkowski, Stephan Hachinger, Florian Dietrich, Ankit Shekhar, Johannes Gensheimer, Adrian Wenzel, and Christoph Gerbig
Atmos. Chem. Phys., 23, 14325–14347, https://doi.org/10.5194/acp-23-14325-2023, https://doi.org/10.5194/acp-23-14325-2023, 2023
Short summary
Short summary
We develop a modeling framework using the Weather Research and Forecasting model at a high spatial resolution (up to 400 m) to simulate atmospheric transport of greenhouse gases and interpret column observations. Output is validated against weather stations and column measurements in August 2018. The differential column method is applied, aided by air-mass transport tracing with the Stochastic Time-Inverted Lagrangian Transport (STILT) model, also for an exploratory measurement interpretation.
Foteini Stavropoulou, Katarina Vinković, Bert Kers, Marcel de Vries, Steven van Heuven, Piotr Korbeń, Martina Schmidt, Julia Wietzel, Pawel Jagoda, Jaroslav M. Necki, Jakub Bartyzel, Hossein Maazallahi, Malika Menoud, Carina van der Veen, Sylvia Walter, Béla Tuzson, Jonas Ravelid, Randulph Paulo Morales, Lukas Emmenegger, Dominik Brunner, Michael Steiner, Arjan Hensen, Ilona Velzeboer, Pim van den Bulk, Hugo Denier van der Gon, Antonio Delre, Maklawe Essonanawe Edjabou, Charlotte Scheutz, Marius Corbu, Sebastian Iancu, Denisa Moaca, Alin Scarlat, Alexandru Tudor, Ioana Vizireanu, Andreea Calcan, Magdalena Ardelean, Sorin Ghemulet, Alexandru Pana, Aurel Constantinescu, Lucian Cusa, Alexandru Nica, Calin Baciu, Cristian Pop, Andrei Radovici, Alexandru Mereuta, Horatiu Stefanie, Alexandru Dandocsi, Bas Hermans, Stefan Schwietzke, Daniel Zavala-Araiza, Huilin Chen, and Thomas Röckmann
Atmos. Chem. Phys., 23, 10399–10412, https://doi.org/10.5194/acp-23-10399-2023, https://doi.org/10.5194/acp-23-10399-2023, 2023
Short summary
Short summary
In this study, we quantify CH4 emissions from onshore oil production sites in Romania at source and facility level using a combination of ground- and drone-based measurement techniques. We show that the total CH4 emissions in our studied areas are much higher than the emissions reported to UNFCCC, and up to three-quarters of the detected emissions are related to operational venting. Our results suggest that oil and gas production infrastructure in Romania holds a massive mitigation potential.
Truls Andersen, Zhao Zhao, Marcel de Vries, Jaroslaw Necki, Justyna Swolkien, Malika Menoud, Thomas Röckmann, Anke Roiger, Andreas Fix, Wouter Peters, and Huilin Chen
Atmos. Chem. Phys., 23, 5191–5216, https://doi.org/10.5194/acp-23-5191-2023, https://doi.org/10.5194/acp-23-5191-2023, 2023
Short summary
Short summary
The Upper Silesian Coal Basin, Poland, is one of the hot spots of methane emissions in Europe. Using an uncrewed aerial vehicle (UAV), we performed atmospheric measurements of methane concentrations downwind of five ventilation shafts in this region and determined the emission rates from the individual shafts. We found a strong correlation between quantified shaft-averaged emission rates and hourly inventory data, which also allows us to estimate the methane emissions from the entire region.
Dominik Brunner, Gerrit Kuhlmann, Stephan Henne, Erik Koene, Bastian Kern, Sebastian Wolff, Christiane Voigt, Patrick Jöckel, Christoph Kiemle, Anke Roiger, Alina Fiehn, Sven Krautwurst, Konstantin Gerilowski, Heinrich Bovensmann, Jakob Borchardt, Michal Galkowski, Christoph Gerbig, Julia Marshall, Andrzej Klonecki, Pascal Prunet, Robert Hanfland, Margit Pattantyús-Ábrahám, Andrzej Wyszogrodzki, and Andreas Fix
Atmos. Chem. Phys., 23, 2699–2728, https://doi.org/10.5194/acp-23-2699-2023, https://doi.org/10.5194/acp-23-2699-2023, 2023
Short summary
Short summary
We evaluated six atmospheric transport models for their capability to simulate the CO2 plumes from two of the largest power plants in Europe by comparing the models against aircraft observations collected during the CoMet (Carbon Dioxide and Methane Mission) campaign in 2018. The study analyzed how realistically such plumes can be simulated at different model resolutions and how well the planned European satellite mission CO2M will be able to quantify emissions from power plants.
Justyna Swolkień, Andreas Fix, and Michał Gałkowski
Atmos. Chem. Phys., 22, 16031–16052, https://doi.org/10.5194/acp-22-16031-2022, https://doi.org/10.5194/acp-22-16031-2022, 2022
Short summary
Short summary
Determination of emissions from coal mines on a local scale requires instantaneous data. We analysed temporal emission data for ventilation shafts and factors influencing their variability. They were saturation of the seams with methane, the permeability of the rock mass, and coal output. The data for the verification should reflect the actual values of emissions from point sources. It is recommended to achieve this by using a standardised emission measurement system for all coal mines.
Sourish Basu, Xin Lan, Edward Dlugokencky, Sylvia Michel, Stefan Schwietzke, John B. Miller, Lori Bruhwiler, Youmi Oh, Pieter P. Tans, Francesco Apadula, Luciana V. Gatti, Armin Jordan, Jaroslaw Necki, Motoki Sasakawa, Shinji Morimoto, Tatiana Di Iorio, Haeyoung Lee, Jgor Arduini, and Giovanni Manca
Atmos. Chem. Phys., 22, 15351–15377, https://doi.org/10.5194/acp-22-15351-2022, https://doi.org/10.5194/acp-22-15351-2022, 2022
Short summary
Short summary
Atmospheric methane (CH4) has been growing steadily since 2007 for reasons that are not well understood. Here we determine sources of methane using a technique informed by atmospheric measurements of CH4 and its isotopologue 13CH4. Measurements of 13CH4 provide for better separation of microbial, fossil, and fire sources of methane than CH4 measurements alone. Compared to previous assessments such as the Global Carbon Project, we find a larger microbial contribution to the post-2007 increase.
Vishnu Thilakan, Dhanyalekshmi Pillai, Christoph Gerbig, Michal Galkowski, Aparnna Ravi, and Thara Anna Mathew
Atmos. Chem. Phys., 22, 15287–15312, https://doi.org/10.5194/acp-22-15287-2022, https://doi.org/10.5194/acp-22-15287-2022, 2022
Short summary
Short summary
This paper demonstrates how we can use atmospheric observations to improve the CO2 flux estimates in India. This is achieved by improving the representation of terrain, mesoscale transport, and flux variations. We quantify the impact of the unresolved variations in the current models on optimally estimated fluxes via inverse modelling and quantify the associated flux uncertainty. We illustrate how a parameterization scheme captures this variability in the coarse models.
Malika Menoud, Carina van der Veen, Dave Lowry, Julianne M. Fernandez, Semra Bakkaloglu, James L. France, Rebecca E. Fisher, Hossein Maazallahi, Mila Stanisavljević, Jarosław Nęcki, Katarina Vinkovic, Patryk Łakomiec, Janne Rinne, Piotr Korbeń, Martina Schmidt, Sara Defratyka, Camille Yver-Kwok, Truls Andersen, Huilin Chen, and Thomas Röckmann
Earth Syst. Sci. Data, 14, 4365–4386, https://doi.org/10.5194/essd-14-4365-2022, https://doi.org/10.5194/essd-14-4365-2022, 2022
Short summary
Short summary
Emission sources of methane (CH4) can be distinguished with measurements of CH4 stable isotopes. We present new measurements of isotope signatures of various CH4 sources in Europe, mainly anthropogenic, sampled from 2017 to 2020. The present database also contains the most recent update of the global signature dataset from the literature. The dataset improves CH4 source attribution and the understanding of the global CH4 budget.
Qiansi Tu, Matthias Schneider, Frank Hase, Farahnaz Khosrawi, Benjamin Ertl, Jaroslaw Necki, Darko Dubravica, Christopher J. Diekmann, Thomas Blumenstock, and Dianjun Fang
Atmos. Chem. Phys., 22, 9747–9765, https://doi.org/10.5194/acp-22-9747-2022, https://doi.org/10.5194/acp-22-9747-2022, 2022
Short summary
Short summary
Three-year satellite observations and high-resolution model forecast of XCH4 are used to derive CH4 emissions in the USCB region, Poland – a region of intense coal mining activities. The wind-assigned anomalies for two opposite wind directions are calculated and the estimated emission rates are very close to the inventories and in reasonable agreement with the previous studies. Our method is quite robust and can serve as a simple method to estimate CH4 or CO2 emissions for other regions.
Saqr Munassar, Christian Rödenbeck, Frank-Thomas Koch, Kai U. Totsche, Michał Gałkowski, Sophia Walther, and Christoph Gerbig
Atmos. Chem. Phys., 22, 7875–7892, https://doi.org/10.5194/acp-22-7875-2022, https://doi.org/10.5194/acp-22-7875-2022, 2022
Short summary
Short summary
The results obtained from ensembles of inversions over 13 years show the largest spread in the a posteriori fluxes over the station set ensemble. Using different prior fluxes in the inversions led to a smaller impact. Drought occurrences in 2018 and 2019 affected CO2 fluxes as seen in net ecosystem exchange estimates. Our study highlights the importance of expanding the atmospheric site network across Europe to better constrain CO2 fluxes in inverse modelling.
Andreas Luther, Julian Kostinek, Ralph Kleinschek, Sara Defratyka, Mila Stanisavljević, Andreas Forstmaier, Alexandru Dandocsi, Leon Scheidweiler, Darko Dubravica, Norman Wildmann, Frank Hase, Matthias M. Frey, Jia Chen, Florian Dietrich, Jarosław Nȩcki, Justyna Swolkień, Christoph Knote, Sanam N. Vardag, Anke Roiger, and André Butz
Atmos. Chem. Phys., 22, 5859–5876, https://doi.org/10.5194/acp-22-5859-2022, https://doi.org/10.5194/acp-22-5859-2022, 2022
Short summary
Short summary
Coal mining is an extensive source of anthropogenic methane emissions. In order to reduce and mitigate methane emissions, it is important to know how much and where the methane is emitted. We estimated coal mining methane emissions in Poland based on atmospheric methane measurements and particle dispersion modeling. In general, our emission estimates suggest higher emissions than expected by previous annual emission reports.
Sven Krautwurst, Konstantin Gerilowski, Jakob Borchardt, Norman Wildmann, Michał Gałkowski, Justyna Swolkień, Julia Marshall, Alina Fiehn, Anke Roiger, Thomas Ruhtz, Christoph Gerbig, Jaroslaw Necki, John P. Burrows, Andreas Fix, and Heinrich Bovensmann
Atmos. Chem. Phys., 21, 17345–17371, https://doi.org/10.5194/acp-21-17345-2021, https://doi.org/10.5194/acp-21-17345-2021, 2021
Short summary
Short summary
Quantification of anthropogenic CH4 emissions remains challenging, but it is essential for near-term climate mitigation strategies. We use airborne remote sensing observations to assess bottom-up estimates of coal mining emissions from one of Europe's largest CH4 emission hot spots located in Poland. The analysis reveals that emissions from small groups of shafts can be disentangled, but caution is advised when comparing observations to commonly reported annual emissions.
Anna K. Tobler, Alicja Skiba, Francesco Canonaco, Griša Močnik, Pragati Rai, Gang Chen, Jakub Bartyzel, Miroslaw Zimnoch, Katarzyna Styszko, Jaroslaw Nęcki, Markus Furger, Kazimierz Różański, Urs Baltensperger, Jay G. Slowik, and Andre S. H. Prevot
Atmos. Chem. Phys., 21, 14893–14906, https://doi.org/10.5194/acp-21-14893-2021, https://doi.org/10.5194/acp-21-14893-2021, 2021
Short summary
Short summary
Kraków is among the cities with the highest particulate matter levels within Europe. We conducted long-term and highly time-resolved measurements of the chemical composition of submicron particlulate matter (PM1). Combined with advanced source apportionment techniques, which allow for time-dependent factor profiles, our results elucidate that traffic and residential heating (biomass burning and coal combustion) as well as oxygenated organic aerosol are the key PM sources in Kraków.
Malika Menoud, Carina van der Veen, Jaroslaw Necki, Jakub Bartyzel, Barbara Szénási, Mila Stanisavljević, Isabelle Pison, Philippe Bousquet, and Thomas Röckmann
Atmos. Chem. Phys., 21, 13167–13185, https://doi.org/10.5194/acp-21-13167-2021, https://doi.org/10.5194/acp-21-13167-2021, 2021
Short summary
Short summary
Using measurements of methane isotopes in ambient air and a 3D atmospheric transport model, in Krakow, Poland, we mainly detected fossil-fuel-related sources, coming from coal mining in Silesia and from the use of natural gas in the city. Emission inventories report large emissions from coal mine activity in Silesia, which is in agreement with our measurements. However, methane sources in the urban area of Krakow related to the use of fossil fuels might be underestimated in the inventories.
Piotr Sekuła, Anita Bokwa, Jakub Bartyzel, Bogdan Bochenek, Łukasz Chmura, Michał Gałkowski, and Mirosław Zimnoch
Atmos. Chem. Phys., 21, 12113–12139, https://doi.org/10.5194/acp-21-12113-2021, https://doi.org/10.5194/acp-21-12113-2021, 2021
Short summary
Short summary
The wind shear generated on a local scale by the diversified relief’s impact can be a factor which significantly modifies the spatial pattern of PM10 concentration. The vertical profile of PM10 over a city located in a large valley during the events with high surface-level PM10 concentrations may show a sudden decrease with height not only due to the increase in wind speed, but also due to the change in wind direction alone. Vertical aerosanitary urban zones can be distinguished.
Vishnu Thilakan, Dhanyalekshmi Pillai, Christoph Gerbig, Michal Galkowski, Aparnna Ravi, and Thara Anna Mathew
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-392, https://doi.org/10.5194/acp-2021-392, 2021
Revised manuscript not accepted
Short summary
Short summary
This paper demonstrates how we can make use of atmospheric observations to improve the CO2 flux estimates of India. This is achieved by improving the representation of terrain, mesoscale transport and flux variations. We quantify the impact of unresolved variations in the current models on optimally estimated fluxes via inverse modelling and quantify the associated flux uncertainty. We illustrate how a parameterization scheme captures this variability in the coarse models.
Cited articles
Andersen, T., Scheeren, B., Peters, W., and Chen, H.: A UAV-based active AirCore system for measurements of greenhouse gases, Atmos. Meas. Tech., 11, 2683–2699, https://doi.org/10.5194/amt-11-2683-2018, 2018. a, b
Ashworth, K., Bucci, S., Gallimore, P. J., Lee, J., Nelson, B. S., Sanchez-Marroquín, A., Schimpf, M. B., Smith, P. D., Drysdale, W. S., Hopkins, J. R., Lee, J. D., Pitt, J. R., Di Carlo, P., Krejci, R., and McQuaid, J. B.: Megacity and local contributions to regional air pollution: an aircraft case study over London, Atmos. Chem. Phys., 20, 7193–7216, https://doi.org/10.5194/acp-20-7193-2020, 2020. a
Bergamaschi, P., Corazza, M., Karstens, U., Athanassiadou, M., Thompson, R. L., Pison, I., Manning, A. J., Bousquet, P., Segers, A., Vermeulen, A. T., Janssens-Maenhout, G., Schmidt, M., Ramonet, M., Meinhardt, F., Aalto, T., Haszpra, L., Moncrieff, J., Popa, M. E., Lowry, D., Steinbacher, M., Jordan, A., O'Doherty, S., Piacentino, S., and Dlugokencky, E.: Top-down estimates of European CH4 and N2O emissions based on four different inverse models, Atmos. Chem. Phys., 15, 715–736, https://doi.org/10.5194/acp-15-715-2015, 2015. a
Bolek, A., Heimann, M., and Göckede, M.: UAV-based in situ measurements of CO2 and CH4 fluxes over complex natural ecosystems, Atmos. Meas. Tech., 17, 5619–5636, https://doi.org/10.5194/amt-17-5619-2024, 2024. a
Cambaliza, M. O. L., Shepson, P. B., Caulton, D. R., Stirm, B., Samarov, D., Gurney, K. R., Turnbull, J., Davis, K. J., Possolo, A., Karion, A., Sweeney, C., Moser, B., Hendricks, A., Lauvaux, T., Mays, K., Whetstone, J., Huang, J., Razlivanov, I., Miles, N. L., and Richardson, S. J.: Assessment of uncertainties of an aircraft-based mass balance approach for quantifying urban greenhouse gas emissions, Atmos. Chem. Phys., 14, 9029–9050, https://doi.org/10.5194/acp-14-9029-2014, 2014. a
Chen, J., Dietrich, F., Forstmaier, A., Bettinelli, J., Maazallahi, H., Schneider, C., Röckmann, T., Winkler, D., Zhao, X., Makowski, M., Klappenbach, F., van der Veen, C., Wildmann, N., Jones, T., Ament, F., Lange, I., Denier van der Gon, H., and Schwietzke, S.: Multi-scale measurements combined with inverse modeling for assessing methane emissions of Hamburg, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11548, https://doi.org/10.5194/egusphere-egu22-11548, 2022. a
de Foy, B., Schauer, J. J., Lorente, A., and Borsdorff, T.: Investigating high methane emissions from urban areas detected by TROPOMI and their association with untreated wastewater, Environ. Res. Lett., 18, 044004, https://doi.org/10.1088/1748-9326/acc118, 2023. a
Dietrich, F., Chen, J., Voggenreiter, B., Aigner, P., Nachtigall, N., and Reger, B.: MUCCnet: Munich Urban Carbon Column network, Atmos. Meas. Tech., 14, 1111–1126, https://doi.org/10.5194/amt-14-1111-2021, 2021. a
Duren, R. M. and Miller, C. E.: Measuring the carbon emissions of megacities, Nat. Clim. Change, 2, 560–562, https://doi.org/10.1038/nclimate1629, 2012. a
ECMWF: COCO2 Project Website, https://coco2-project.eu/ (last access: 15 February 2026), 2026. a
EEA: Industrial Reporting under the Industrial Emissions Directive 2010/75/EU and European Pollutant Release and Transfer Register Regulation (EC) No. 166/2006 – ver. 10.0 Dec 2023 (Tabular data), https://doi.org/10.2909/63a14e09-d1f5-490d-80cf-6921e4e69551, 2023. a
Enting, I. G., Trudinger, C. M., and Francey, R. J.: A synthesis inversion of the concentration and δ13C of atmospheric CO2, Tellus B, 47, 35–52, https://doi.org/10.1034/j.1600-0889.47.issue1.5.x, 1995. a
Fiehn, A., Kostinek, J., Eckl, M., Klausner, T., Gałkowski, M., Chen, J., Gerbig, C., Röckmann, T., Maazallahi, H., Schmidt, M., Korbeń, P., Neçki, J., Jagoda, P., Wildmann, N., Mallaun, C., Bun, R., Nickl, A.-L., Jöckel, P., Fix, A., and Roiger, A.: Estimating CH4, CO2 and CO emissions from coal mining and industrial activities in the Upper Silesian Coal Basin using an aircraft-based mass balance approach, Atmos. Chem. Phys., 20, 12675–12695, https://doi.org/10.5194/acp-20-12675-2020, 2020. a, b
Gałkowski, M., Jordan, A., Rothe, M., Marshall, J., Koch, F.-T., Chen, J., Agusti-Panareda, A., Fix, A., and Gerbig, C.: In situ observations of greenhouse gases over Europe during the CoMet 1.0 campaign aboard the HALO aircraft, Atmos. Meas. Tech., 14, 1525–1544, https://doi.org/10.5194/amt-14-1525-2021, 2021. a
Gerbig, C., Lin, J. C., Wofsy, S. C., Daube, B. C., Andrews, A. E., Stephens, B. B., Bakwin, P. S., and Grainger, C. A.: Toward constraining regional-scale fluxes of CO2 with atmospheric observations over a continent: 1. Observed spatial variability from airborne platforms, J. Geophys. Res.-Atmos., 108, https://doi.org/10.1029/2002JD003018, 2003. a
Giovannini, L., Ferrero, E., Karl, T., Rotach, M. W., Staquet, C., Trini Castelli, S., and Zardi, D.: Atmospheric Pollutant Dispersion over Complex Terrain: Challenges and Needs for Improving Air Quality Measurements and Modeling, Atmosphere, 11, https://doi.org/10.3390/atmos11060646, 2020. a
Hedworth, H., Page, J., Sohl, J., and Saad, T.: Investigating Errors Observed during UAV-Based Vertical Measurements Using Computational Fluid Dynamics, Drones, 6, https://doi.org/10.3390/drones6090253, 2022. a, b
Heimburger, A. M. F., Harvey, R. M., Shepson, P. B., Stirm, B. H., Gore, C., Turnbull, J., Cambaliza, M. O. L., Salmon, O. E., Kerlo, A.-E. M., Lavoie, T. N., Davis, K. J., Lauvaux, T., Karion, A., Sweeney, C., Brewer, W. A., Hardesty, R. M., and Gurney, K. R.: Assessing the optimized precision of the aircraft mass balance method for measurement of urban greenhouse gas emission rates through averaging, Elem. Sci. Anth., 5, 26, https://doi.org/10.1525/elementa.134, 2017. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate, Copernicus Climate Change Service (C3S) Data Store (CDS) [data set], https://doi.org/10.24381/cds.143582cf, 2017. a
Honnert, R., Efstathiou, G. A., Beare, R. J., Ito, J., Lock, A., Neggers, R., Plant, R. S., Shin, H. H., Tomassini, L., and Zhou, B.: The Atmospheric Boundary Layer and the “Gray Zone” of Turbulence: A Critical Review, J. Geophys. Res.-Atmos., 125, e2019JD030317, https://doi.org/10.1029/2019JD030317, 2020. a
ICOS-Cities: https://www.icos-cp.eu/projects/icos-cities (last access: 14 February 2026), 2026. a
ICOS RI: ICOS Atmosphere Station Specifications V2.0, edited by: Laurent, O., Tech. rep., ICOS Research Infrastructure, https://doi.org/10.18160/GK28-2188, 2020. a
IEA: World Energy Outlook, Chap. 8, International Energy Agency, 179–193, ISBN 978926404560-6, https://iea.blob.core.windows.net/assets/89d1f68c-f4bf-4597-805f-901cfa6ce889/weo2008.pdf (last access: 20 April 2026), 2008. a
IMGW-PIB: IMGW-PIB forecasts, https://meteo.imgw.pl (last access: 2 June 2023), 2023. a
IPCC: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC, Geneva, Switzerland, 35–115, https://doi.org/10.59327/IPCC/AR6-9789291691647, 2023. a
Jasek-Kamińska, A., Zimnoch, M., Wachniew, P., and Różański, K.: Urban CO2 Budget: Spatial and Seasonal Variability of CO2 Emissions in Krakow, Poland, Atmosphere, 11, https://doi.org/10.3390/atmos11060629, 2020. a
Klausner, T., Mertens, M., Huntrieser, H., Galkowski, M., Kuhlmann, G., Baumann, R., Fiehn, A., Jöckel, P., Pühl, M., and Roiger, A.: Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO2 and CH4 in situ observations in summer 2018, Elem. Sci. Anth., 8, https://doi.org/10.1525/elementa.411, 15, 2020. a
Kotthaus, S., Haeffelin, M., Drouin, M.-A., Dupont, J.-C., Grimmond, S., Haefele, A., Hervo, M., Poltera, Y., and Wiegner, M.: Tailored Algorithms for the Detection of the Atmospheric Boundary Layer Height from Common Automatic Lidars and Ceilometers (ALC), Remote Sens., 12, https://doi.org/10.3390/rs12193259, 2020. a
Krings, T., Neininger, B., Gerilowski, K., Krautwurst, S., Buchwitz, M., Burrows, J. P., Lindemann, C., Ruhtz, T., Schüttemeyer, D., and Bovensmann, H.: Airborne remote sensing and in situ measurements of atmospheric CO2 to quantify point source emissions, Atmos. Meas. Tech., 11, 721–739, https://doi.org/10.5194/amt-11-721-2018, 2018. a
Kunz, M., Lavric, J. V., Gerbig, C., Tans, P., Neff, D., Hummelgård, C., Martin, H., Rödjegård, H., Wrenger, B., and Heimann, M.: COCAP: a carbon dioxide analyser for small unmanned aircraft systems, Atmos. Meas. Tech., 11, 1833–1849, https://doi.org/10.5194/amt-11-1833-2018, 2018. a, b
Lampert, A., Pätzold, F., Asmussen, M. O., Lobitz, L., Krüger, T., Rausch, T., Sachs, T., Wille, C., Sotomayor Zakharov, D., Gaus, D., Bansmer, S., and Damm, E.: Studying boundary layer methane isotopy and vertical mixing processes at a rewetted peatland site using an unmanned aircraft system, Atmos. Meas. Tech., 13, 1937–1952, https://doi.org/10.5194/amt-13-1937-2020, 2020. a
Lauvaux, T., Miles, N. L., Richardson, S. J., Deng, A., Stauffer, D. R., Davis, K. J., Jacobson, G., Rella, C., Calonder, G.-P., and DeCola, P. L.: Urban Emissions of CO2 from Davos, Switzerland: The First Real-Time Monitoring System Using an Atmospheric Inversion Technique, J. Appl. Meteorol. Clim., 52, 2654–2668, https://doi.org/10.1175/JAMC-D-13-038.1, 2013. a
Lauvaux, T., Miles, N. L., Deng, A., Richardson, S. J., Cambaliza, M. O., Davis, K. J., Gaudet, B., Gurney, K. R., Huang, J., O'Keefe, D., Song, Y., Karion, A., Oda, T., Patarasuk, R., Razlivanov, I., Sarmiento, D., Shepson, P., Sweeney, C., Turnbull, J., and Wu, K.: High-resolution atmospheric inversion of urban CO2 emissions during the dormant season of the Indianapolis Flux Experiment (INFLUX), J. Geophys. Res.-Atmos., 121, 5213–5236, https://doi.org/10.1002/2015JD024473, 2016. a, b
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. a, b
Lopez-Coto, I., Hicks, M., Karion, A., Sakai, R. K., Demoz, B., Prasad, K., and Whetstone, J.: Assessment of Planetary Boundary Layer Parameterizations and Urban Heat Island Comparison: Impacts and Implications for Tracer Transport, J. Appl. Meteorol. Clim., 59, 1637–1653, https://doi.org/10.1175/JAMC-D-19-0168.1, 2020a. a, b, c
Lopez-Coto, I., Ren, X., Salmon, O. E., Karion, A., Shepson, P. B., Dickerson, R. R., Stein, A., Prasad, K., and Whetstone, J. R.: Wintertime CO2, CH4, and CO Emissions Estimation for the Washington, DC–Baltimore Metropolitan Area Using an Inverse Modeling Technique, Environ. Sci. Technol., 54, 2606–2614, https://doi.org/10.1021/acs.est.9b06619, 2020b. a
Lowry, D., Holmes, C. W., Rata, N. D., O'Brien, P., and Nisbet, E. G.: London methane emissions: Use of diurnal changes in concentration and δ13C to identify urban sources and verify inventories, J. Geophys. Res.-Atmos., 106, 7427–7448, https://doi.org/10.1029/2000JD900601, 2001. a, b
Mays, K. L., Shepson, P. B., Stirm, B. H., Karion, A., Sweeney, C., and Gurney, K. R.: Aircraft-Based Measurements of the Carbon Footprint of Indianapolis, Environ. Sci. Technol., 43, 7816–7823, https://doi.org/10.1021/es901326b, 2009. a
McKinney, K. A., Wang, D., Ye, J., de Fouchier, J.-B., Guimarães, P. C., Batista, C. E., Souza, R. A. F., Alves, E. G., Gu, D., Guenther, A. B., and Martin, S. T.: A sampler for atmospheric volatile organic compounds by copter unmanned aerial vehicles, Atmos. Meas. Tech., 12, 3123–3135, https://doi.org/10.5194/amt-12-3123-2019, 2019. a
Menoud, M., van der Veen, C., Necki, J., Bartyzel, J., Szénási, B., Stanisavljević, M., Pison, I., Bousquet, P., and Röckmann, T.: Methane (CH4) sources in Krakow, Poland: insights from isotope analysis, Atmos. Chem. Phys., 21, 13167–13185, https://doi.org/10.5194/acp-21-13167-2021, 2021. a
Nalini, K., Lauvaux, T., Abdallah, C., Lian, J., Ciais, P., Utard, H., Laurent, O., and Ramonet, M.: High-Resolution Lagrangian Inverse Modeling of CO2 Emissions Over the Paris Region During the First 2020 Lockdown Period, J. Geophys. Res.-Atmos., 127, e2021JD036032, https://doi.org/10.1029/2021JD036032, 2022. a
Nautical Almanac Office: Almanac for computers, United States Naval Observatory, Washington, DC, https://gml.noaa.gov/grad/solcalc/sunrise.html (last access: 20 April 2026), 1990. a
NOAA: Trends in Atmospheric Carbon Dioxide, https://www.noaa.gov/news-release/greenhouse-gases-continued-to-increase-rapidly-in-2022 (last access: 15 May 2024), 2024. a
NOAA ARL: Hysplit-web (internet-based) by NOAA Air Resources Laboratory, https://www.ready.noaa.gov/HYSPLIT.php (last access: 16 February 2026), 2026. a
Ou, Y., Roney, C., Alsalam, J., Calvin, K., Creason, J., Edmonds, J., Fawcett, A. A., Kyle, P., Narayan, K., O'Rourke, P., Patel, P., Ragnauth, S., Smith, S. J., and McJeon, H.: Deep mitigation of CO2 and non-CO2 greenhouse gases toward 1.5 °C and 2 °C futures, Nat. Commun., 12, 6245, https://doi.org/10.1038/s41467-021-26509-z, 2021. a
Park, H., Jeong, S., Sha, M. K., Lee, J., and Frey, M. M.: Comparisons of Greenhouse Gas Observation Satellite Performances Over Seoul Using a Portable Ground-Based Spectrometer, Geophys. Res. Lett., 51, e2024GL109334, https://doi.org/10.1029/2024GL109334, 2024. a
Peng, Y., Hu, C., Ai, X., Li, Y., Gao, L., Liu, H., Zhang, J., and Xiao, W.: Improvements of Simulating Urban Atmospheric CO2 Concentration by Coupling with Emission Height and Dynamic Boundary Layer Variations in WRF-STILT Model, Atmosphere, 14, https://doi.org/10.3390/atmos14020223, 2023. a
Ponomarev, N., Steiner, M., Koene, E., Rubli, P., Grange, S., Constantin, L., Ramonet, M., David, L., Hamzehloo, A., Emmenegger, L., and Brunner, D.: Estimation of CO2 fluxes in the cities of Zurich and Paris using the ICON-ART CTDAS inverse modelling framework, Atmos. Chem. Phys., 26, 547–570, https://doi.org/10.5194/acp-26-547-2026, 2026. a
Reum, F., Gerbig, C., Lavric, J. V., Rella, C. W., and Göckede, M.: Correcting atmospheric CO2 and CH4 mole fractions obtained with Picarro analyzers for sensitivity of cavity pressure to water vapor, Atmos. Meas. Tech., 12, 1013–1027, https://doi.org/10.5194/amt-12-1013-2019, 2019. a
Richardson, S. J., Miles, N. L., Davis, K. J., Lauvaux, T., Martins, D. K., Turnbull, J. C., McKain, K., Sweeney, C., and Cambaliza, M. O. L.: Tower measurement network of in-situ CO2, CH4, and CO in support of the Indianapolis FLUX (INFLUX) Experiment, Elem. Sci. Anth., 5, 59, https://doi.org/10.1525/elementa.140, 2017. a
Rödenbeck, C., Houweling, S., Gloor, M., and Heimann, M.: CO2 flux history 1982–2001 inferred from atmospheric data using a global inversion of atmospheric transport, Atmos. Chem. Phys., 3, 1919–1964, https://doi.org/10.5194/acp-3-1919-2003, 2003. a
Rózanski, K., Chmura, L., Galkowski, M., Necki, J., Zimnoch, M., Bartyzel, J., and O'Doherty, S.: Monitoring of Greenhouse Gases in the Atmosphere – A Polish Perspective, International Geosphere Biospehere Programme: A Study of Global Change. Papers on Global Change IGBP, 23, 111–126, https://doi.org/10.1515/igbp-2016-0009, 2016. a
Sekuła, P., Bokwa, A., Bartyzel, J., Bochenek, B., Chmura, Ł., Gałkowski, M., and Zimnoch, M.: Measurement report: Effect of wind shear on PM10 concentration vertical structure in the urban boundary layer in a complex terrain, Atmos. Chem. Phys., 21, 12113–12139, https://doi.org/10.5194/acp-21-12113-2021, 2021a. a
Sekuła, P., Bokwa, A., Ustrnul, Z., Zimnoch, M., and Bochenek, B.: The impact of a foehn wind on PM10 concentrations and the urban boundary layer in complex terrain: a case study from Kraków, Poland, Tellus B, https://doi.org/10.1080/16000889.2021.1933780, 2021b. a
Sekuła, P., Zimnoch, M., Bartyzel, J., Bokwa, A., Kud, M., and Necki, J.: Ultra-Light Airborne Measurement System for Investigation of Urban Boundary Layer Dynamics, Sensors, 21, https://doi.org/10.3390/s21092920, 2021c. a
Seto, K., Dhakal, S., Bigio, A., Blanco, H., Delgado, G. C., Dewar, D., Huang, L., Inaba, A., Kansal, A., Lwasa, S., McMahon, J., Müller, D. B., Murakami, J., Nagendra, H., and Ramaswami, A.: Human Settlements, Infrastructure and Spatial Planning, in: Climate Change 2014: Mitigation of Climate Change, Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Farahani, E., Kadner, S., Seyboth, K., Adler, A., Baum, I., Brunner, S., Eickemeier, P., Kriemann, B., Savolainen, J., Schlömer, S., von Stechow, C., Zwickel, T., and Minx, J. C., Cambridge University Press, Cambridge, UK and New York, NY, USA, ISBN 978-1-107-05821-7, https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_chapter12.pdf (last access: 20 April 2026), 2014. a
Stein, A. F., Draxler, R. R., Rolph, G. D., Stunder, B. J. B., Cohen, M. D., and Ngan, F.: NOAA's HYSPLIT Atmospheric Transport and Dispersion Modeling System, B. Am. Meteorol. Soc., 96, 2059–2077, https://doi.org/10.1175/BAMS-D-14-00110.1, 2015. a
Turnbull, J. C., Karion, A., Fischer, M. L., Faloona, I., Guilderson, T., Lehman, S. J., Miller, B. R., Miller, J. B., Montzka, S., Sherwood, T., Saripalli, S., Sweeney, C., and Tans, P. P.: Assessment of fossil fuel carbon dioxide and other anthropogenic trace gas emissions from airborne measurements over Sacramento, California in spring 2009, Atmos. Chem. Phys., 11, 705–721, https://doi.org/10.5194/acp-11-705-2011, 2011. a, b, c
UN: Paris Agreement to the United Nations Framework Convention on Climate Change, 12 December 2015, TIAS No. 16–1104, 2015. a
United Nations Environment Programme: Emissions Gap Report 2025: Off Target – Continued Collective inaction puts Global Temperature Goal at Risk, https://doi.org/10.59117/20.500.11822/48854, 2025. a
USK: Urząd Statystyczny w Krakowie, https://krakow.stat.gov.pl/ (last access: 2 June 2023), 2023. a
van der Woude, A. M., de Kok, R., Smith, N., Luijkx, I. T., Botía, S., Karstens, U., Kooijmans, L. M. J., Koren, G., Meijer, H. A. J., Steeneveld, G.-J., Storm, I., Super, I., Scheeren, H. A., Vermeulen, A., and Peters, W.: Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling, Earth Syst. Sci. Data, 15, 579–605, https://doi.org/10.5194/essd-15-579-2023, 2023. a
WMO: Integrated Global Greenhouse Gas Information System: Urban Emission Observation and Monitoring Good Research Practice Guidelines, GAW Report No. 314, https://doi.org/10.59327/WMO/GAW/314, 2025. a
Wolff, S., Ehret, G., Kiemle, C., Amediek, A., Quatrevalet, M., Wirth, M., and Fix, A.: Determination of the emission rates of CO2 point sources with airborne lidar, Atmos. Meas. Tech., 14, 2717–2736, https://doi.org/10.5194/amt-14-2717-2021, 2021. a
Zhang, L., Davis, K. J., Schuh, A. E., Jacobson, A. R., Pal, S., Cui, Y. Y., Baker, D., Crowell, S., Chevallier, F., Remaud, M., Liu, J., Weir, B., Philip, S., Johnson, M. S., Deng, F., and Basu, S.: Multi-Season Evaluation of CO2 Weather in OCO-2 MIP Models, J. Geophys. Res.-Atmos., 127, e2021JD035457, https://doi.org/10.1029/2021JD035457, 2022. a
Zhou, Y., Qiao, C., Zhou, M., Wang, Y., Tian, X., Wang, Y., and Duan, M.: Observation of greenhouse gas vertical profiles in the boundary layer of the Mount Qomolangma region using a multirotor UAV, Atmos. Meas. Tech., 18, 1609–1619, https://doi.org/10.5194/amt-18-1609-2025, 2025. a
Zimnoch, M., Florkowski, T., Necki, J. M., and Neubert, R. E. M.: Diurnal variability of δ13C and δ18O of atmospheric CO2 in the urban atmosphere of Kraków, Poland, Isot. Environ. Healt. S., 40, 129–143, https://doi.org/10.1080/10256010410001670989, 2004. a
Zimnoch, M., Necki, J., Chmura, L., Jasek, A., Jelen, D., Galkowski, M., Kuc, T., Gorczyca, Z., Bartyzel, J., and Rozanski, K.: Quantification of carbon dioxide and methane emissions in urban areas: source apportionment based on atmospheric observations, Mitig. Adapt. Strat. Gl., 24, 1051–1071, https://doi.org/10.1007/s11027-018-9821-0, 2019. a
Zimnoch, M., Sekula, P., Jasek-Kaminska, A., Skiba, A., Gałkowski, M., Chmura, L., Bartyzel, J., Jagoda, P., Kud, M., and Necki, J.: Observational datasets of urban CO2 fluxes, atmospheric vertical profiles of CO2 and CH4 and 14CO2, and isotopic composition of atmospheric CO2 at Krakow, Poland; period 2021–2023; part of the CoCO2 project, AGH University of Krakow, ICOS Carbon Portal [data set], https://doi.org/10.18160/8DSK-R4JS, 2023. a
Short summary
The manuscript presents the dataset collected in the urban area of Krakow city containing several measurement campaigns focused on the investigation of vertical CO2 and CH4 profiles supplemented by set of meteorological parameters (e.g. temperature, pressure) measured along the profiles up to ca. 280 m a.g.l. The presented data collection explains the dynamics of the lower atmosphere on a daily and seasonal scale providing the three dimensional dataset that can be used for model validation.
The manuscript presents the dataset collected in the urban area of Krakow city containing...
Altmetrics
Final-revised paper
Preprint