Best practices and uncertainties in CH4 emission quantification: employing mobile measurements and Gaussian plume modelling at a biogas plant
The increasing number of biogas plants in Germany and Europe necessitate an appropriate strategy to quantify potential methane (CH4) losses to ensure the sustainability of renewable energy production. In addition to high uncertainties in emission factors, there is little information on the temporal...
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| Hauptverfasser: | , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
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23 September 2025
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| In: |
Atmospheric measurement techniques
Year: 2025, Jahrgang: 18, Heft: 18, Pages: 4631-4645 |
| ISSN: | 1867-8548 |
| DOI: | 10.5194/amt-18-4631-2025 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.5194/amt-18-4631-2025 Verlag, lizenzpflichtig, Volltext: https://amt.copernicus.org/articles/18/4631/2025/ 
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| Verfasserangaben: | Julia Beate Wietzel, Piotr Korben, Antje Hoheisel, and Martina Schmidt |
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| 520 | |a The increasing number of biogas plants in Germany and Europe necessitate an appropriate strategy to quantify potential methane (CH4) losses to ensure the sustainability of renewable energy production. In addition to high uncertainties in emission factors, there is little information on the temporal variation in CH4 emissions from biogas plants. In this study, long-term measurements of CH4 emission rates at a biogas plant in Heidelberg, Germany, were performed over a period of 8 years using mobile measurements combined with a Gaussian plume model (GPM). To increase the accuracy of the emission rate calculations and harmonize the dataset, the methodology was evaluated through six controlled methane release experiments. The results of these experiments demonstrated that our method exhibits an uncertainty lower than 30 %, provided that the following recommendations are followed: wind and solar radiation should be measured on site, at least 10 transects should be driven at low speeds, and a minimum distance of 20 m should be maintained from the emission source. By integrating these improvements into long-term monitoring practices at a biogas plant in Heidelberg, we present a comprehensive and consistent dataset of mobile measurements from 26 campaigns. The data revealed only low temporal variations in CH4 emission rates, which is probably due to the continuous operation of the biogas plant with stable procedures. Notably, the average CH4 emission rate was 5.9 ± 0.5 kg CH4 h−1. The successful integration of data acquired over 8 years through multiple measurement setups increases the reliability of the dataset, providing valuable insights into methane emissions from biogas plants. | ||
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