Advancements in satellite-based methane point source monitoring: A systematic review

Methane (CH4) stands out as the second-largest contributor to the global warming since pre-industrial era. Anthropogenic methane emissions (e.g., oil and gas, waste management, and coal mining) are the major sources of methane release and in the meantime provide an excellent opportunity for emission reduction. Regarding this, observations from satellite remote sensing paly pivotal role in methane detection and quantification, further enhancing the temporal and spatial extent of methane research. A key feature of satellite data is the presence of Shortwave Infrared (SWIR) methane absorption bands, which are essential for identifying methane plumes from space. Detection, monitoring, and characterization are the main components of satellite-based methane studies. In general, quantifying methane emissions from regional and point sources presents two major challenges in the literature and the past few years have witnessed a tremendous success in terms of research, development, and operationalization of new techniques for methane studies, particularly, in the latter domain. As such, there is a need for a systematic analysis and review of existing literature to identify current trends, techniques, earth observation data for methane point source monitoring from space. Accordingly, this study systematically reviews 77 studies and highlights the critical roles of satellite data in detecting methane point source emissions. The literature identifies oil and gas sector as a dominant source of reported methane emission, particularly from countries like Turkmenistan, the United States, and Algeria. The review also categorizes instruments with methane detection capabilities into three main types, namely hyperspectral, multispectral, and SWIR spectrometers, each offering their unique advantages and addressing the limitations of other source of data. The main processing steps for methane point source emission monitoring from space identified in the literature are methane column retrieval, masking/detection, and source rate quantification. The literature reveals while conventional techniques are still widely used for methane detection and quantification, AI-based models are emerging as useful tools in different stages of methane research and significantly address the limitations of conventional techniques. The general characteristics of methane point source studies reveal a diverse array of applications across both atmospheric science and remote sensing fields. The rising number of publications in these areas, especially in high-impact journals, underscores the importance and relevance of methane monitoring. These studies bridge the gap between atmospheric observations and remote sensing technologies, contributing to a more integrated understanding of methane emissions on a global scale.