FI-SCAPE: A Divergence Theorem Based Emission Quantification Model for Air&#x002F;Spaceborne Imaging Spectrometer Derived X<sub>CH4</sub> Observations

The Global Methane Pledge calls for a reduction of methane emissions by at least 30&#x0025; by 2030. The reduction of methane emissions in the energy sector is critical to achieving this target. Remote sensing plays a crucial role in identifying and quantifying methane superemitters. In the fort...

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Main Authors: Yiyang Huang, Ge Han, Tianqi Shi, Siwei Li, Huiqin Mao, Yihuang Nie, Wei Gong
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Online Access:https://ieeexplore.ieee.org/document/10742394/
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author Yiyang Huang
Ge Han
Tianqi Shi
Siwei Li
Huiqin Mao
Yihuang Nie
Wei Gong
author_facet Yiyang Huang
Ge Han
Tianqi Shi
Siwei Li
Huiqin Mao
Yihuang Nie
Wei Gong
author_sort Yiyang Huang
collection DOAJ
description The Global Methane Pledge calls for a reduction of methane emissions by at least 30&#x0025; by 2030. The reduction of methane emissions in the energy sector is critical to achieving this target. Remote sensing plays a crucial role in identifying and quantifying methane superemitters. In the forthcoming years, multiple promising missions carrying imaging spectrometers will be sent into orbit to obtain XCH4 observations with extensive coverage and high resolution. Traditional emission quantification models, such as the Gaussian plume model and some based on chemical transport models, are not optimally suited to the characteristics of new data. In this article, we propose a divergence-theorem-based emission quantification model, named flux integration method based on sinusoidal cosine optimization algorithm to inverse the methane point source emissions, which utilizes XCH4 observations derived from airborne imaging spectrometers to achieve rapid and accurate estimation of methane point source emission rates. This approach overcomes limitations of other methods, such as the inability of Gaussian plume models to recover the integrity of regional concentration enhancements, excessive disruption caused by integrated mass enhancement and divergence integral masking operators, and the requirement for effective wind speed fitting. The extraction of plume regions only causes a perturbation of approximately &#x00B1;5&#x0025; in the results, and the <italic>R</italic> value of this method on real datasets exceeds 0.89. It provides technical support for rapid and accurate monitoring of methane point source emissions on a global scale, aiding in the establishment of routine methane emission monitoring systems based on satellite remote sensing.
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publishDate 2025-01-01
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series IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
spelling doaj-art-f13afd5f2f33430fa1e29a2e930f09732024-11-29T00:00:41ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-011825527210.1109/JSTARS.2024.349089610742394FI-SCAPE: A Divergence Theorem Based Emission Quantification Model for Air&#x002F;Spaceborne Imaging Spectrometer Derived X<sub>CH4</sub> ObservationsYiyang Huang0https://orcid.org/0009-0008-9362-1725Ge Han1https://orcid.org/0000-0003-2561-3244Tianqi Shi2https://orcid.org/0000-0003-4815-4175Siwei Li3Huiqin Mao4Yihuang Nie5Wei Gong6https://orcid.org/0000-0002-2276-8024Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaHubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaLaboratoire des Sciences du Climat et de l&#x0027;Environnement, LSCE&#x002F;IPSL, CEA-CNRS-UVSQ, Universite&#x0301; Paris-Saclay, Gif-sur-Yvette, FranceHubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaMinistry of Ecology and Environment Center for Satellite Application on Ecology and Environment&#x002F;State Environmental Protection Key Laboratory of Satellite Remote Sensing, Beijing, ChinaMinistry of Ecology and Environment Center for Satellite Application on Ecology and Environment&#x002F;State Environmental Protection Key Laboratory of Satellite Remote Sensing, Beijing, ChinaElectronic Information School, Wuhan University, Wuhan, ChinaThe Global Methane Pledge calls for a reduction of methane emissions by at least 30&#x0025; by 2030. The reduction of methane emissions in the energy sector is critical to achieving this target. Remote sensing plays a crucial role in identifying and quantifying methane superemitters. In the forthcoming years, multiple promising missions carrying imaging spectrometers will be sent into orbit to obtain XCH4 observations with extensive coverage and high resolution. Traditional emission quantification models, such as the Gaussian plume model and some based on chemical transport models, are not optimally suited to the characteristics of new data. In this article, we propose a divergence-theorem-based emission quantification model, named flux integration method based on sinusoidal cosine optimization algorithm to inverse the methane point source emissions, which utilizes XCH4 observations derived from airborne imaging spectrometers to achieve rapid and accurate estimation of methane point source emission rates. This approach overcomes limitations of other methods, such as the inability of Gaussian plume models to recover the integrity of regional concentration enhancements, excessive disruption caused by integrated mass enhancement and divergence integral masking operators, and the requirement for effective wind speed fitting. The extraction of plume regions only causes a perturbation of approximately &#x00B1;5&#x0025; in the results, and the <italic>R</italic> value of this method on real datasets exceeds 0.89. It provides technical support for rapid and accurate monitoring of methane point source emissions on a global scale, aiding in the establishment of routine methane emission monitoring systems based on satellite remote sensing.https://ieeexplore.ieee.org/document/10742394/Divergenceflux integration method based on sinusoidal cosine optimization algorithm to inverse the methane point source emissions (FI-SCAPE)methane emissionspoint source
spellingShingle Yiyang Huang
Ge Han
Tianqi Shi
Siwei Li
Huiqin Mao
Yihuang Nie
Wei Gong
FI-SCAPE: A Divergence Theorem Based Emission Quantification Model for Air&#x002F;Spaceborne Imaging Spectrometer Derived X<sub>CH4</sub> Observations
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Divergence
flux integration method based on sinusoidal cosine optimization algorithm to inverse the methane point source emissions (FI-SCAPE)
methane emissions
point source
title FI-SCAPE: A Divergence Theorem Based Emission Quantification Model for Air&#x002F;Spaceborne Imaging Spectrometer Derived X<sub>CH4</sub> Observations
title_full FI-SCAPE: A Divergence Theorem Based Emission Quantification Model for Air&#x002F;Spaceborne Imaging Spectrometer Derived X<sub>CH4</sub> Observations
title_fullStr FI-SCAPE: A Divergence Theorem Based Emission Quantification Model for Air&#x002F;Spaceborne Imaging Spectrometer Derived X<sub>CH4</sub> Observations
title_full_unstemmed FI-SCAPE: A Divergence Theorem Based Emission Quantification Model for Air&#x002F;Spaceborne Imaging Spectrometer Derived X<sub>CH4</sub> Observations
title_short FI-SCAPE: A Divergence Theorem Based Emission Quantification Model for Air&#x002F;Spaceborne Imaging Spectrometer Derived X<sub>CH4</sub> Observations
title_sort fi scape a divergence theorem based emission quantification model for air x002f spaceborne imaging spectrometer derived x sub ch4 sub observations
topic Divergence
flux integration method based on sinusoidal cosine optimization algorithm to inverse the methane point source emissions (FI-SCAPE)
methane emissions
point source
url https://ieeexplore.ieee.org/document/10742394/
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