Space-ground integration system of methane emission monitoring and quantification: cases in Dongying, China
Calibrating traditional inventory-based emission estimates with top-down point source inversion results is of significant importance. To address the challenges posed by satellite remote sensing in accurately assessing methane point source emissions and the inefficiency of ground-based mobile measure...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Earth Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2025.1577961/full |
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| author | Hu He Dong Sun Jingang Zhao Xin Yuan Haoran Li Fang Liu Wei Wang |
| author_facet | Hu He Dong Sun Jingang Zhao Xin Yuan Haoran Li Fang Liu Wei Wang |
| author_sort | Hu He |
| collection | DOAJ |
| description | Calibrating traditional inventory-based emission estimates with top-down point source inversion results is of significant importance. To address the challenges posed by satellite remote sensing in accurately assessing methane point source emissions and the inefficiency of ground-based mobile measurement due to the lack of prior information, this paper proposes a novel space-ground integration system of methane emission monitoring and quantification. The system utilizes a classic matched filter (CMF) algorithm to retrieve greenhouse gas concentration increments from multi-temporal hyperspectral images, thereby identifying continuous point sources, which subsequently guides the development of ground-based emission data collection plans. The EMISSION-PARTITION model is applied to quantify point source emission intensities. In April 2024, our team conducted an experiment based on this system in a petrochemical industrial park in Dongying, China. Satellite observations identified key continuous point sources with an uncertainty of 8.08%. The point source emission intensities quantified from mobile measurement ranged from a minimum of 139.36 kg/hto a maximum of 107.42 kg/h, with uncertainties controlled within 19.1%. This experiment provides valuable insights for similar greenhouse gas emission monitoring and quantification tasks. |
| format | Article |
| id | doaj-art-b6854241ebe44428850a2d06f74496fb |
| institution | DOAJ |
| issn | 2296-6463 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Earth Science |
| spelling | doaj-art-b6854241ebe44428850a2d06f74496fb2025-08-20T03:10:13ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632025-06-011310.3389/feart.2025.15779611577961Space-ground integration system of methane emission monitoring and quantification: cases in Dongying, ChinaHu He0Dong Sun1Jingang Zhao2Xin Yuan3Haoran Li4Fang Liu5Wei Wang6Technical Test Centre of Sinopec Shengli Oil Field, Dongying, ChinaTechnical Test Centre of Sinopec Shengli Oil Field, Dongying, ChinaTechnical Test Centre of Sinopec Shengli Oil Field, Dongying, ChinaTechnical Test Centre of Sinopec Shengli Oil Field, Dongying, ChinaTechnical Test Centre of Sinopec Shengli Oil Field, Dongying, ChinaTechnical Test Centre of Sinopec Shengli Oil Field, Dongying, ChinaSchool of Geosciences and Info-Physics, Central South University, Changsha, ChinaCalibrating traditional inventory-based emission estimates with top-down point source inversion results is of significant importance. To address the challenges posed by satellite remote sensing in accurately assessing methane point source emissions and the inefficiency of ground-based mobile measurement due to the lack of prior information, this paper proposes a novel space-ground integration system of methane emission monitoring and quantification. The system utilizes a classic matched filter (CMF) algorithm to retrieve greenhouse gas concentration increments from multi-temporal hyperspectral images, thereby identifying continuous point sources, which subsequently guides the development of ground-based emission data collection plans. The EMISSION-PARTITION model is applied to quantify point source emission intensities. In April 2024, our team conducted an experiment based on this system in a petrochemical industrial park in Dongying, China. Satellite observations identified key continuous point sources with an uncertainty of 8.08%. The point source emission intensities quantified from mobile measurement ranged from a minimum of 139.36 kg/hto a maximum of 107.42 kg/h, with uncertainties controlled within 19.1%. This experiment provides valuable insights for similar greenhouse gas emission monitoring and quantification tasks.https://www.frontiersin.org/articles/10.3389/feart.2025.1577961/fullspace-ground integrationmatched filterin-situ measurementCH4 emissionsatellite |
| spellingShingle | Hu He Dong Sun Jingang Zhao Xin Yuan Haoran Li Fang Liu Wei Wang Space-ground integration system of methane emission monitoring and quantification: cases in Dongying, China Frontiers in Earth Science space-ground integration matched filter in-situ measurement CH4 emission satellite |
| title | Space-ground integration system of methane emission monitoring and quantification: cases in Dongying, China |
| title_full | Space-ground integration system of methane emission monitoring and quantification: cases in Dongying, China |
| title_fullStr | Space-ground integration system of methane emission monitoring and quantification: cases in Dongying, China |
| title_full_unstemmed | Space-ground integration system of methane emission monitoring and quantification: cases in Dongying, China |
| title_short | Space-ground integration system of methane emission monitoring and quantification: cases in Dongying, China |
| title_sort | space ground integration system of methane emission monitoring and quantification cases in dongying china |
| topic | space-ground integration matched filter in-situ measurement CH4 emission satellite |
| url | https://www.frontiersin.org/articles/10.3389/feart.2025.1577961/full |
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