A fast and efficient method for calculation of background methane concentrations using Sentinel-5P satellite data

Plamen Trenchev; Maria Dimitrova; Daniela Avetisyan; Temenuzhka Spasova

doi:10.1117/12.2681793

21 September 2023 A fast and efficient method for calculation of background methane concentrations using Sentinel-5P satellite data

Plamen Trenchev, Maria Dimitrova, Daniela Avetisyan, Temenuzhka Spasova

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Proceedings Volume 12786, Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023); 1278624 (2023) https://doi.org/10.1117/12.2681793
Event: Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 2023, Ayia Napa, Cyprus

Abstract

Increased emissions and thus higher concentrations of greenhouse gases in the atmosphere as a result of human activities are one of the main reasons for the observed rise in temperatures in recent years. Methane is the second most abundant greenhouse gas and plays a significant role in global warming. With the oil and gas industry and coal mining accounting for the majority of anthropogenic emissions, atmospheric methane concentrations are increasing at an accelerating rate. In this paper, using satellite data from the Sentinel-5P for the period of May 2018 to December 2022, we present an efficient and fast method to calculate background atmospheric CH4 concentrations. The emission source in the study area is homogeneous, allowing the proposed method to be used as a benchmark for building models to estimate and track emissions in heterogeneous regions. The knowledge of background concentrations allows the tracking of seasonal and annual variations and trends, as well as the rapid detection of regular or accidental emissions from unregulated sources.

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Plamen Trenchev, Maria Dimitrova, Daniela Avetisyan, and Temenuzhka Spasova "A fast and efficient method for calculation of background methane concentrations using Sentinel-5P satellite data", Proc. SPIE 12786, Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 1278624 (21 September 2023); https://doi.org/10.1117/12.2681793

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