Articles | Volume 20, issue 6
https://doi.org/10.5194/acp-20-3683-2020
© Author(s) 2020. 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-20-3683-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
27 Mar 2020
Research article | Highlight paper |
| 27 Mar 2020
| 27 Mar 2020
Methane emissions from the Munich Oktoberfest
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Institute for Advanced Study, Technical University of Munich, Garching, Germany
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Hossein Maazallahi
Institute for Marine and Atmospheric research Utrecht, Utrecht University, Utrecht, the Netherlands
Climate, Air and Sustainability, TNO, Utrecht, the Netherlands
Andreas Forstmaier
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Dominik Winkler
Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
Magdalena E. G. Hofmann
Picarro B.V., 's-Hertogenbosch, the Netherlands
Hugo Denier van der Gon
Climate, Air and Sustainability, TNO, Utrecht, the Netherlands
Thomas Röckmann
Institute for Marine and Atmospheric research Utrecht, Utrecht University, Utrecht, the Netherlands
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Cited
18 citations as recorded by crossref.
- Anthropogenic CO2 emissions assessment of Nile Delta using XCO2 and SIF data from OCO-2 satellite A. Shekhar et al. 10.1088/1748-9326/ab9cfe
- Photoacoustic methane detection inside a MEMS microphone T. Strahl et al. 10.1016/j.pacs.2022.100428
- Methane mapping, emission quantification, and attribution in two European cities: Utrecht (NL) and Hamburg (DE) H. Maazallahi et al. 10.5194/acp-20-14717-2020
- MUCCnet: Munich Urban Carbon Column network F. Dietrich et al. 10.5194/amt-14-1111-2021
- Improved calibration procedures for the EM27/SUN spectrometers of the COllaborative Carbon Column Observing Network (COCCON) C. Alberti et al. 10.5194/amt-15-2433-2022
- A Novel Gas Recognition and Concentration Detection Algorithm for Artificial Olfaction W. Zhang et al. 10.1109/TIM.2021.3071313
- Minimal PM2.5 Impact Observed in Communities Near Large, Recurring, Non-Independence Day Festivals with Fireworks Displays V. Lang & J. Kahl 10.3390/air1010001
- Quantification of methane emissions in Hamburg using a network of FTIR spectrometers and an inverse modeling approach A. Forstmaier et al. 10.5194/acp-23-6897-2023
- Spatiotemporal modeling of air pollutant concentrations in Germany using machine learning V. Balamurugan et al. 10.5194/acp-23-10267-2023
- Methane emissions from above-ground natural gas distribution facilities in the urban environment: A fence line methodology and case study in Calgary, Alberta, Canada C. Hugenholtz et al. 10.1080/10962247.2021.1942316
- Methodologies for Measuring Microbial Methane Production and Emission from Soils—A Review M. Glagolev et al. 10.1134/S0026261721010057
- Pyra: Automated EM27/SUN Greenhouse Gas Measurement Software P. Aigner et al. 10.21105/joss.05131
- Modeling temporal variability in the surface expression above a methane leak: The ESCAPE model S. Riddick et al. 10.1016/j.jngse.2021.104275
- Assessing urban methane emissions using column-observing portable Fourier transform infrared (FTIR) spectrometers and a novel Bayesian inversion framework T. Jones et al. 10.5194/acp-21-13131-2021
- Climate Impact Comparison of Electric and Gas‐Powered End‐User Appliances F. Dietrich et al. 10.1029/2022EF002877
- Using controlled subsurface releases to investigate the effect of leak variation on above-ground natural gas detection M. Mbua et al. 10.1016/j.jgsce.2023.205153
- Transmission and Distribution Pipeline Leak Identification and Characterization by Walking Survey and Soil Flux Measurements E. Robinson & P. DeCarlo 10.1021/acsestair.4c00109
- Practical paths towards quantifying and mitigating agricultural methane emissions E. Nisbet et al. 10.1098/rspa.2024.0390
18 citations as recorded by crossref.
- Anthropogenic CO2 emissions assessment of Nile Delta using XCO2 and SIF data from OCO-2 satellite A. Shekhar et al. 10.1088/1748-9326/ab9cfe
- Photoacoustic methane detection inside a MEMS microphone T. Strahl et al. 10.1016/j.pacs.2022.100428
- Methane mapping, emission quantification, and attribution in two European cities: Utrecht (NL) and Hamburg (DE) H. Maazallahi et al. 10.5194/acp-20-14717-2020
- MUCCnet: Munich Urban Carbon Column network F. Dietrich et al. 10.5194/amt-14-1111-2021
- Improved calibration procedures for the EM27/SUN spectrometers of the COllaborative Carbon Column Observing Network (COCCON) C. Alberti et al. 10.5194/amt-15-2433-2022
- A Novel Gas Recognition and Concentration Detection Algorithm for Artificial Olfaction W. Zhang et al. 10.1109/TIM.2021.3071313
- Minimal PM2.5 Impact Observed in Communities Near Large, Recurring, Non-Independence Day Festivals with Fireworks Displays V. Lang & J. Kahl 10.3390/air1010001
- Quantification of methane emissions in Hamburg using a network of FTIR spectrometers and an inverse modeling approach A. Forstmaier et al. 10.5194/acp-23-6897-2023
- Spatiotemporal modeling of air pollutant concentrations in Germany using machine learning V. Balamurugan et al. 10.5194/acp-23-10267-2023
- Methane emissions from above-ground natural gas distribution facilities in the urban environment: A fence line methodology and case study in Calgary, Alberta, Canada C. Hugenholtz et al. 10.1080/10962247.2021.1942316
- Methodologies for Measuring Microbial Methane Production and Emission from Soils—A Review M. Glagolev et al. 10.1134/S0026261721010057
- Pyra: Automated EM27/SUN Greenhouse Gas Measurement Software P. Aigner et al. 10.21105/joss.05131
- Modeling temporal variability in the surface expression above a methane leak: The ESCAPE model S. Riddick et al. 10.1016/j.jngse.2021.104275
- Assessing urban methane emissions using column-observing portable Fourier transform infrared (FTIR) spectrometers and a novel Bayesian inversion framework T. Jones et al. 10.5194/acp-21-13131-2021
- Climate Impact Comparison of Electric and Gas‐Powered End‐User Appliances F. Dietrich et al. 10.1029/2022EF002877
- Using controlled subsurface releases to investigate the effect of leak variation on above-ground natural gas detection M. Mbua et al. 10.1016/j.jgsce.2023.205153
- Transmission and Distribution Pipeline Leak Identification and Characterization by Walking Survey and Soil Flux Measurements E. Robinson & P. DeCarlo 10.1021/acsestair.4c00109
- Practical paths towards quantifying and mitigating agricultural methane emissions E. Nisbet et al. 10.1098/rspa.2024.0390
Discussed (final revised paper)
Latest update: 25 Mar 2025
Short summary
We demonstrate for the first time that large festivals can be significant methane sources, though they are not included in emission inventories. We combined in situ measurements with a Gaussian plume model to determine the Oktoberfest emissions and show that they are not due solely to human biogenic emissions, but are instead primarily fossil fuel related. Our study provides the foundation to develop reduction policies for such events and new pathways to mitigate fossil fuel methane emissions.
We demonstrate for the first time that large festivals can be significant methane sources,...
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