Articles | Volume 19, issue 7
https://doi.org/10.5194/amt-19-2343-2026
© 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/amt-19-2343-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Dynamic quantification of methane emissions at facility scale using laser tomography: demonstration of a farm deployment
Department of Technical Physics, University of Eastern Finland, P.O. Box 1627, Kuopio 70211, Finland
Grasslands and Sustainable Farming, Production Systems Unit, Natural Resources Institute Finland, Halolantie 31A, Maaninka, Kuopio 71750, Finland
Elias Vänskä
Department of Technical Physics, University of Eastern Finland, P.O. Box 1627, Kuopio 70211, Finland
Damien Weidmann
Space Science and Technology Department, STFC Rutherford Appleton Laboratory, Harwell Campus, Didcot OX11 0QX, UK
Mirico Ltd., Eighth street, Harwell Campus, Didcot OX11 0RL, UK
Aku Ursin
Department of Technical Physics, University of Eastern Finland, P.O. Box 1627, Kuopio 70211, Finland
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Alexander Kurganskiy, Liang Feng, Neil Humpage, Paul I. Palmer, A. Jerome P. Woodwark, Stamatia Doniki, and Damien Weidmann
Atmos. Meas. Tech., 18, 7525–7563, https://doi.org/10.5194/amt-18-7525-2025, https://doi.org/10.5194/amt-18-7525-2025, 2025
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This study introduces GEMINI-UK (Greenhouse gas Emissions Monitoring network to Inform Net-zero Initiatives for the UK), the first UK-wide network using ground-based instruments to monitor net fluxes of CO2 and methane. By simulating its performance, we show that GEMINI-UK will significantly reduce uncertainties in these flux estimates, complementing data from existing tall towers and future satellite missions. The network will strengthen the UK's ability to track greenhouse gases, evaluate climate policies, and meet net-zero goals.
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.
Oliver Schneising, Heinrich Bovensmann, Michael Buchwitz, Matthias Buschmann, Nicholas M. Deutscher, David W. T. Griffith, Jonas Hachmeister, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Hirofumi Ohyama, Christof Petri, Maximilian Reuter, John Robinson, Coleen Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Wei Wang, Thorsten Warneke, Damien Weidmann, Debra Wunch, Minqiang Zhou, and Hartmut Bösch
EGUsphere, https://doi.org/10.5194/egusphere-2025-5422, https://doi.org/10.5194/egusphere-2025-5422, 2025
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We present an improved version of the TROPOMI/WFMD algorithm for the simultaneous retrieval of atmospheric methane and carbon monoxide from satellite observations. The updated data product combines higher data yield with better precision and accuracy, expanding its suitability for a wider range of scientific applications. These substantial advances are mainly due to refined quality filtering, enabling more reliable identification of cloudy scenes and mitigating specific aerosol-related issues.
Damien Weidmann, Richard Brownsword, and Stamatia Doniki
Geosci. Instrum. Method. Data Syst., 14, 113–129, https://doi.org/10.5194/gi-14-113-2025, https://doi.org/10.5194/gi-14-113-2025, 2025
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The development and characterization of a ground-based system measuring column average concentrations of greenhouse gases is described, as well as the corresponding four years dataset recorded at Harwell, Oxfordshire, UK. The system, based on high-resolution Fourier Transform spectroscopy of atmospheric transmission, fulfills the requirements established by the Total Carbon Column Observatory Network (TCCON) to contribute to the international greenhouse gas observing infrastructure.
Yunsong Liu, Jean-Daniel Paris, Gregoire Broquet, Violeta Bescós Roy, Tania Meixus Fernandez, Rasmus Andersen, Andrés Russu Berlanga, Emil Christensen, Yann Courtois, Sebastian Dominok, Corentin Dussenne, Travis Eckert, Andrew Finlayson, Aurora Fernández de la Fuente, Catlin Gunn, Ram Hashmonay, Juliano Grigoleto Hayashi, Jonathan Helmore, Soeren Honsel, Fabrizio Innocenti, Matti Irjala, Torgrim Log, Cristina Lopez, Francisco Cortés Martínez, Jonathan Martinez, Adrien Massardier, Helle Gottschalk Nygaard, Paula Agregan Reboredo, Elodie Rousset, Axel Scherello, Matthias Ulbricht, Damien Weidmann, Oliver Williams, Nigel Yarrow, Murès Zarea, Robert Ziegler, Jean Sciare, Mihalis Vrekoussis, and Philippe Bousquet
Atmos. Meas. Tech., 17, 1633–1649, https://doi.org/10.5194/amt-17-1633-2024, https://doi.org/10.5194/amt-17-1633-2024, 2024
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We investigated the performance of 10 methane emission quantification techniques in a blind controlled-release experiment at an inerted natural gas compressor station. We reported their respective strengths, weaknesses, and potential complementarity depending on the emission rates and atmospheric conditions. Additionally, we assess the dependence of emission quantification performance on key parameters such as wind speed, deployment constraints, and measurement duration.
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Short summary
We present a laser-based tomographic approach for dynamically quantifying and mapping greenhouse gas emissions at facility scale. It was applied during a campaign at a research farm in Eastern Finland, where methane emissions from typical manure-handling events were monitored. The results show that incorporating prior information on source locations improves the tolerance of the flux estimates with respect to environmental disturbances.
We present a laser-based tomographic approach for dynamically quantifying and mapping greenhouse...