인공위성 원격탐사 기반 메탄 배출 모니터링 기술 현황 = Current Status of Satellite Remote Sensing-Based Methane Emission Monitoring Technologies

국문 초록 (Abstract)

메탄은 이산화탄소에 이어 두 번째로 지구온난화에 미치는 영향이 큰 온실가스로, 기후변화에 상당한 영향을 미친다. 본 논문에서는 메탄 배출을 효율적으로 탐지하고 정량화하기 위해 사용되는 인공위성 원격탐사 기반 메탄 탐지 기술을 종합적으로 검토하고자 한다. 메탄 배출원은 크게 자연적 배출원(영구동토, 습지)과 인위적 배출원(농축산업, 석탄광, 석유 및 가스전, 폐기물 처리)으로 구분된다. 이 중 인위적 배출원에 대해 단파장적외선을 포함한 다양한 파장영역의 정보를 활용한 메탄 탐지의 원리와 이를 지원하는 주요 위성자료의 활용성에 대해 고찰하였다. 최근에는 위성자료를 활용한 메탄 탐지에서 딥러닝 기법을 적용한 연구들이 진행되고 있으며 이는 메탄 배출을 보다 정확하게 분석하는 데 기여하고 있다. 또한, 딥러닝 기법 적용 사례를 포함하여 전 지구, 지역 및 대형 사고 규모에서의 메탄 배출 탐지 사례를 종합적으로 검토하고 위성 기반 메탄 모니터링의 실용성을 평가하였다. 전 지구 규모에서는 Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI)와 같은 위성 센서를 사용한 연구들이 검토되었고 지역 규모에서는 주로 TROPOMI 자료와 상대적으로 고해상도의 위성자료(Sentinel-2 MultiSpectral Instrument (MSI), GHGSat Wide-Angle Fabry-Perot (WAF-P) Imaging Spectrometer 등)를 결합하여 메탄 배출 및 배출량을 탐지한 연구 사례를 소개하였다. 이러한 종합적 검토를 통해 위성 기반 메탄 탐지 기술의 현황과 활용성을 평가하였다.

다국어 초록 (Multilingual 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.

참고문헌 (Reference)

• 1 국립농업과학원, "농경지 온실가스 자동측정 및 배출량품질관리 기법 연구" 농촌진흥청 2021
• 2 Maasakkers, J. D., "Using satellites to uncover large methane emissions from landfills" 8 (8): 2022
• 3 Joyce, P., "Using a deep neural network to detect methane point sources and quantify emissions from PRISMA hyperspectral satellite images" 16 (16): 2627-2640, 2023
• 4 Gorroño, J., "Understanding the potential of Sentinel-2 for monitoring methane point emissions" 16 (16): 89-107, 2023
• 5 Jongaramrungruang, S., "Towards accurate methane point-source quantification from high-resolution 2-D plume imagery" 12 (12): 6667-6681, 2019
• 6 Karakurt, I., "Sources and mitigation of methane emissions by sectors: A Critical Review" 39 (39): 40-48, 2012
• 7 Sanderson, K., "September 30) What do Nord Stream methane leaks mean for climate change?" 2022
• 8 Dogniaux, M., "Report on Landsat 8 and Sentinel-2B observations of the Nord Stream 2 pipeline methane leak" 17 (17): 2777-2787, 2024
• 9 Varon, D. J., "Quantifying time-averaged methane emissions from individual coal mine vents with GHGSat-D satellite observations" 54 (54): 10246-10253, 2020
• 10 Varon, D. J., "Quantifying methane point sources from fine-scale satellite observations of atmospheric methane plumes" 11 (11): 5673-5686, 2018
• 11 Cusworth, D. H., "Potential of next-generation imaging spectrometers to detect and quantify methane point sources from space" 12 (12): 5655-5668, 2019
• 12 Barchyn, T. E., "Plume detection modeling of a drone-based natural gas leak detection system" 7 (7): 2019
• 13 Liu, Y., "On-line monitoring of methane in sewer air" 4 (4): 2014
• 14 Yakovlev, S. V., "Mobile Airborne Lidar for Remote Methane Monitoring: Design, Simulation of Atmospheric Measurements and First Flight Tests" 14 (14): 6355-, 2022
• 15 Van Amstel, A, "Methane. A review" 9 (9): 5-30, 2012
• 16 Chai, X., "Methane emissions as energy reservoir: context, scope, causes and mitigation strategies" 56 : 33-70, 2016
• 17 Sorg, D., "Measuring livestock CH4 emissions with the laser methane detector: A review" 1 (1): 38-57, 2021
• 18 Sánchez-García, E., "Mapping methane plumes at very high spatial resolution with the WorldView-3 satellite" 15 : 1657-1674, 2022
• 19 IEA, "Main sources of methane emissions"
• 20 He, H., "In-situ testing of methane emissions from landfills using laser absorption spectroscopy" 11 (11): 2117-, 2021
• 21 Varon, D. J., "High-frequency monitoring of anomalous methane point sources with multispectral Sentinel-2 satellite observations" 14 (14): 2771-2785, 2021
• 22 Ehret, T., "Global tracking and quantification of oil and gas methane emissions from recurrent sentinel-2 imagery" 56 (56): 10517-10529, 2022
• 23 IEA, "Global methane emissions from the energy sector over time, 2000-2021"
• 24 Lauvaux, T., "Global assessment of oil and gas methane ultra-emitters" 375 (375): 557-561, 2022
• 25 "Global Methane Pledge"
• 26 Wang, H., "Exploiting the Matched Filter to Improve the Detection of Methane Plumes with Sentinel-2 Data" 16 (16): 1023-, 2024
• 27 Pandey, S., "Daily detection and quantification of methane leaks using Sentinel-3: a tiered satellite observation approach with Sentinel-2 and Sentinel-5p" 296 : 113716-, 2023
• 28 Schuur, E. A., "Climate change and the permafrost carbon feedback" 520 (520): 171-179, 2015
• 29 IPCC, "Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change" IPCC 184-, 2023
• 30 IPCC, "Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change" Cambridge University Press 2391-, 2021
• 31 Elder, C. D., "Characterizing methane emission hotspots from thawing permafrost" 35 (35): 2021
• 32 Duren, R. M., "California’s methane super-emitters" 575 (575): 180-184, 2019
• 33 United States Environmental Protection Agency, "Biden-Harris Administration finalizes standards to slash methane pollution, combat climate change, protect health, and bolster American innovation"
• 34 Schuit, B. J., "Automated detection and monitoring of methane superemitters using satellite data" 23 : 9071-9098, 2023
• 35 McLinden, C. A., "An independent evaluation of GHGSat methane emissions:Performance assessment" 129 (129): 2024
• 36 Frankenberg, C., "Airborne methane remote measurements reveal heavy-tail flux distribution in Four Corners region" 113 (113): 9734-9739, 2016