Current Status of Satellite Remote Sensing-Based Methane Emission Monitoring Technologies

Abstract

Methane is the second most significant greenhouse gas contributing to global warming after carbon dioxide, exerting a substantial impact on climate change. This paper provides a comprehensive review of satellite remote sensing-based methane detection technologies used to efficiently detect and quantify methane emissions. Methane emission sources are broadly categorized into natural sources (such as permafrost and wetlands) and anthropogenic sources (such as agriculture, coal mines, oil and gas fields, and landfills). This study focuses on anthropogenic sources and examines the principles of methane detection using information from various spectral bands, including the shortwave infrared (SWIR) band, and the utilization of key satellite data supporting these technologies. Recently, deep learning techniques have been applied in methane detection research using satellite data, contributing to more accurate analyses of methane emissions. Furthermore, this paper assesses the practicality of satellite-based methane monitoring by synthesizing case studies of methane emission detection at global, regional, and major incident scales, including examples of applying deep learning techniques. At the global scale, research utilizing satellite sensors like the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) was reviewed. At the regional scale, studies were highlighted where TROPOMI data was combined with relatively high-resolution satellite data, such as the Sentinel-2 MultiSpectral Instrument (MSI) and GHGSat Wide-Angle Fabry-Perot (WAF-P) Imaging Spectrometer, to detect methane emissions and sources. Through this comprehensive review, the current state and applicability of satellite-based methane detection technologies are evaluated.