Aerosol‐Calibrated Matched Filter Method for Retrievals of Methane Point Source Emissions Over the Los Angeles Basin

Methane, with a global warming potential roughly 86 times greater than carbon dioxide over a 20‐year timeframe, plays a crucial role in global warming. Remote sensing retrieval is a pivotal methodology for identifying methane emission sources, with accuracy influenced largely by surface and atmospheric properties, including aerosols. In this study, we propose an Aerosol‐Calibrated Matched Filter (ACMF) algorithm to improve the traditional Matched Filter (MF) method. Our new approach incorporates an aerosol scattering correction factor to reduce the aerosol‐induced bias on methane retrievals. Validating our algorithm through simulated spectra, we demonstrate that considering the aerosol scattering effect significantly reduces retrieval errors compared to MF methods by an average of approximately 90%. We apply our newly developed algorithm to hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer—Next Generation in the Los Angeles Basin and focus on 11 plumes identified through case studies. Our results reveal that ACMF estimates of emission rates and inversion uncertainties exhibit an average reduction of approximately 4% compared to corresponding MF results, with deviation increasing with aerosol optical depth (AOD). Plain Language Summary Emissions from facilities like oil and gas plants, coal mines, and waste management sites are a major contributor to atmospheric methane, which is a greenhouse gas that significantly impacts global warming. We can remotely measure these emissions using hyperspectral instruments. However, atmospheric particulates (aerosols) can skew these measurements by affecting how sunlight travels through the atmosphere. In our study, we have developed a new, computationally efficient approach to adjust for aerosol effects when analyzing data from these instruments. Tests with simulated data show that our method reduces errors caused by aerosols by about 90% compared with existing schemes. Investigations over 11 different methane emission plumes in the Los Angeles area indicate that traditional methods overestimate methane releases, especially when aerosols are present. Key Points The Aerosol‐Calibrated Matched Filter (ACMF) is proposed for correction of aerosol‐induced bias in methane point source emission retrievals The ACMF method decreased the bias in methane concentration retrieval, demonstrating a clear improvement over the Matched Filter (MF) method The ACMF method, implemented in 11 cases over the