Published Research

Note: This is a preprint, and we expect the final published version to become available soon.

This work demonstrates the capability of MethaneAIR data to be used in tandem with TROPOMI satellite data for inferring methane emissions from an oil and gas basin. The work combines the two instruments using the common platform of the Integrated Methane Inversion (IMI) which is an open source software tool for using computer models of the atmosphere (GOES-Chem) with methane concentration observations to improve knowledge of emissions. We show that estimates of emissions can be improved by including data from both sources.

This study created the first automated artificial intelligence system to find natural gas compressor stations in satellite images. When tested in a large U.S. oil and gas region, the system identified over 1,100 previously unreported facilities, suggesting that existing public databases are missing many sources of pollution. As a result, public exposure to harmful emissions may be underestimated by up to 74%. Results show how machine learning can improve oil and gas infrastructure mapping for tracking and managing methane pollution.

This study created the first automated artificial intelligence system to find natural gas compressor stations in satellite images. When tested in a large U.S. oil and gas region, the system identified over 1,100 previously unreported facilities, suggesting that existing public databases are missing many sources of pollution. As a result, public exposure to harmful emissions may be underestimated by up to 74%. Results show how machine learning can improve oil and gas infrastructure mapping for tracking and managing methane pollution.

A comprehensive assessment of over 400 point source methane emitters detected with MethaneAIR from 2021-2023 across 13 major oil and gas basins covering ~80% of US onshore production was presented in this paper. This was the most geographically extensive survey by an airborne methane imaging spectrometer in a single year and contributes analyses from multiple regions that had not previously been represented in the methane point source literature. Authors describe automated plume-finding methods, perform detailed attribution to facility categories within oil and gas and non-oil and gas sectors, and quantify total point source methane emissions from these basins of 360 t h-1 in 2023, with ~80 % of the total attributable to oil and gas sources.

Presents and validates the retrieval algorithm used by MethaneSAT and MethaneAIR, using MethaneAIR observations over major U.S. oil and gas basins in 2019 and 2021. Repeated surveys reveal both persistent and intermittent high-emitting sources, including a large processing facility with unusually high leak rates and a ruptured pipeline, demonstrating the capability and value of MethaneSAT-style observations for detecting, and quantifying basin-wide methane emissions.

This study presents a sensitive and computationally inexpensive method for detecting methane plumes in MethaneAIR data using a matched-filter algorithm. The performance of the method was demonstrated through comparison with controlled release experiments, comparison with simulated plumes, and intercomparison with other methods. Authors applied this processing chain to MethaneAIR data mosaics acquired over the Permian Basin during flights in 2021 and 2023, which resulted in the detection of hundreds of point sources above 100–200 kg h−1, with a conservative detection limit of around 120 kg h−1.

MethaneSAT conducts monthly lunar calibration scans to ensure the high radiometric accuracy needed to detect and quantify methane emissions around the globe. By using the moon as a stable, well-characterized light source and comparing observations to the European Space Agency’s Lunar Irradiance Model, the team can monitor instrument performance, correct for drift, and strengthen confidence in methane retrievals. Successful lunar scans in 2024 demonstrate the viability of this approach and establish a foundation for long-term calibration trending that supports MethaneSAT’s mission.

This study shows that most U.S. oil and gas-sector methane emissions originate from many facilities that emit at low rates but are widespread. Using sensitive measurement techniques, the authors estimate that ~70% of total oil and gas methane emissions in the continental U.S. in 2021 came from low-emitting upstream and midstream facilities emitting below 100 kg/hour. The findings indicate that addressing only high-emitting sites is insufficient; and that effective methane mitigation must also include the many small, diffuse sources that collectively drive the majority of emissions.

Compiles over 1,500 ground-based facility measurements to develop a high-resolution, measurement-based inventory of 2021 U.S. oil and gas methane emissions. Total methane emissions are estimated to be roughly twice the U.S. EPA Greenhouse Gas Inventory, corresponding to a 2.6% gas-production-normalized methane loss rate, consistent with satellite data. Emissions vary widely by basin, with oil-dominant regions like the Permian, Bakken, and Uinta showing much higher loss rates than gas-dominant regions such as the Appalachian and Haynesville. Comparisons with airborne MethaneAIR data show good agreement with regional estimates and indicate that diffuse sources account for most emissions in key basins.