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Dataset of all TROPOMI detected methane plumes in 2021, including estimates for the source location, emission quantification and source type. Corresponds to Figure 6 of Schuit et al. 2023 [Automated detection and monitoring of methane super-emitters using satellite data, https://doi.org/10.5194/acp-23-9071-2023]. Additional details and context are provided in Section 3 of the paper. Contents and data formats date, date of the TROPOMI observation. format: YYYYMMDD time_UTC, time of the TROPOMI observation in UTC. format: HH:MM:SS lat, latitude of the center of the TROPOMI pixel at the estimated source location. format: float lon, longitude of the center of the TROPOMI pixel at the estimated source location. format: float source_rate_t/h, estimated emission source rate in tonnes per hour, the methodology is described in Section 2.5.1 of the paper. format: int uncertainty_t/h, the uncertainty of the emission source rate in tonnes per hour, the methodology is described in Section 2.5.1 of the paper. format: int estimated_source_type, the locally dominant anthropogenic source sector based on bottom-up inventories, the methodology is described in Section 2.5.3 of the paper. format: str Full citation of the paper: Schuit, B. J., Maasakkers, J. D., Bijl, P., Mahapatra, G., van den Berg, A.-W., Pandey, S., Lorente, A., Borsdorff, T., Houweling, S., Varon, D. J., McKeever, J., Jervis, D., Girard, M., Irakulis-Loitxate, I., Gorroño, J., Guanter, L., Cusworth, D. H., and Aben, I.: Automated detection and monitoring of methane super-emitters using satellite data, Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023, 2023.
TROPOMI, Methane, Plume, Machine learning
TROPOMI, Methane, Plume, Machine learning
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