Estimating Methane Emissions by Integrating Satellite Regional Emissions Mapping and Point-Source Observations: Case Study in the Permian Basin

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Abstract

Methane (CH4) is known as the most potent greenhouse gas in the short term. With the growing urgency of mitigating climate change and monitoring methane emissions, many emerging satellite systems have been launched in the past decade to observe methane and other greenhouse gases from space. These satellites are either capable of pinpointing and quantifying super emitters or deriving regional emissions with a more frequent revisit time. This study aims to reconcile emissions estimated from point source satellites and those from regional mapping satellites, and to investigate the potential of integrating point-based quantification and regional-based quantification techniques. To do that, we quantified methane emissions from the Permian Basin separately by applying the divergence method to the TROPOMI Level-2 data product, as well as an event-based approach using CH₄ plumes quantified by Carbon Mapper systems. The resulted annual CH₄ emissions estimates from the Permian Basin in 2024 are 1.83 ± 0.96 Tg and 1.26 [0.78, 2.02] Tg for divergence and event-based methods, respectively. The divergence-based emissions estimate shows a more comprehensive spatial distribution of emissions across the Permian Basin, whereas the event-based approach highlights the grid cells with the short-duration super-emitters. The emissions from grids with detectable emissions under both methods show strong agreement (R²≈0.642). After substituting the overlap cells’ values from divergence-based emissions estimation with those from event-based estimation, the combined emissions estimate is 2.68 [1.88, 3.54] Tg, which is reconciled with Permian Basin emissions estimates from previous studies. We found that CH₄ emissions from the Permian Basin have been gradually reduced over the past five years. Furthermore, this case study indicates the potential for integrating estimations from both methods to generate a more comprehensive regional emissions estimate.

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