Preprints
https://doi.org/10.5194/amt-2022-261
https://doi.org/10.5194/amt-2022-261
 
04 Oct 2022
04 Oct 2022
Status: this preprint is currently under review for the journal AMT.

Understanding the potential of Sentinel-2 for monitoring methane point emissions

Javier Gorroño1, Daniel J. Varon2, Itziar Irakulis-Loitxate1, and Luis Guanter1,3 Javier Gorroño et al.
  • 1Research Institute of Water and Environmental Engineering (IIAMA), Universitat Politècnica de València, València, Spain
  • 2School of Engineering and Applied Science, Harvard University, Cambridge, 02138, USA
  • 3Environmental Defense Fund, Reguliersgracht 79, 1017 LN Amsterdam, The Netherlands

Abstract. The use of satellite instruments to detect and quantify methane emissions from fossil fuel production activities is highly beneficial to support climate change mitigation. Different hyperspectral and multispectral satellite sensors have recently shown potential to detect and quantify point-source emissions from space. The Sentinel-2 (S2) mission, despite its limited spectral design, supports the detection of large emissions with global coverage and high revisit frequency thanks to coarse spectral coverage of methane absorption lines in the shortwave infrared. Validation of S2 methane retrieval algorithms is instrumental in accelerating the development of a systematic and global monitoring system for methane point sources. Here we develop a benchmarking framework for such validation. We first develop a methodology to generate simulated S2 datasets including methane point-source plumes. These benchmark datasets have been created for scenes in three oil and gas basins (Hassi Messaoud, Algeria; Korpeje, Turkmenistan; Permian Basin, USA) under different scene heterogeneity conditions and for simulated methane plumes with different spatial distributions. We use the simulated methane plumes to validate the retrieval for different flux rate levels and define a minimum detection threshold for each case study. The results suggest that for homogeneous surfaces, the detection limit of the proposed S2 methane retrieval ranges from 1000 kg h−1 to 2000 kg h−1, whereas for areas with large surface heterogeneity, the retrieval can only detect plumes in excess of 5000 kg h−1. The different sources of uncertainty in the flux rate estimates have also been examined. Dominant quantification errors are either wind-related or plume mask-related, depending on the surface type. Uncertainty in wind speed, both in the 10-m wind (U10) and in mapping U10 to the effective wind (Ueff ) driving plume transport, is the dominant source of error for quantifying individual plumes in homogeneous scenes. For heterogeneous scenes, the surface structure underlying the methane plume affects the plume masking and can become a dominant source of uncertainty.

Javier Gorroño et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-261', Cristina Ruiz Villena, 05 Nov 2022
  • RC2: 'Comment on amt-2022-261', Anonymous Referee #2, 07 Nov 2022

Javier Gorroño et al.

Data sets

Sentinel 2 L1C products with simulated methane plumes (S2CH4) Javier Gorroño, Daniel J. Varon, Itziar Irakulis-Loitxate and Luis Guanter https://doi.org/10.7910/DVN/KRNPEH

Javier Gorroño et al.

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Short summary
This work presents a methane flux rate retrieval methodology using the Sentinel-2 mission and validates the algorithm for different scenes and plumes. The detection limit is in the range 1000–2000 kg h−1 for homogeneous surfaces and above 5000 kg h−1 for heterogeneous ones. Dominant quantification errors are either wind-related or plume mask-related. For heterogeneous scenes, the surface structure underlying the methane plume can become a dominant source of uncertainty.