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Spatiotemporal variations and data comparison of CH4 concentrations in north China based on TROPOMI
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Meng-yuan LI1, 2, Jun LI1, 2, *, Wei CHEN2, Bei-jing XIE3, Cheng-ye ZHANG1, 2, Ya-xin DING2, Yue-Jun HUANG4
China Environmental Science | 2025, 45(10) : 5378 - 5389
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China Environmental Science | 2025, 45(10): 5378-5389
• Air Pollution Control •
Spatiotemporal variations and data comparison of CH4 concentrations in north China based on TROPOMI
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Meng-yuan LI1, 2, Jun LI1, 2, *, Wei CHEN2, Bei-jing XIE3, Cheng-ye ZHANG1, 2, Ya-xin DING2, Yue-Jun HUANG4
Affiliations
  • 1.Inner Mongolia Research Institute, China University of Mining and Technology-Beijing, Erdos 017010, China
  • 2.College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
  • 3.College of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
  • 4.Guoneng Beidian Shengli Energy Co., Ltd., Xilinhot 026000, China
Published: 2025-10-20
Outline
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Methane (CH4), as a short-lived and high-warming potential greenhouse gas, understanding its concentration distribution and changes is crucial for China to achieve its "Dual Carbon" goal. This study systematically analyzed the distribution and changing pattern of methane concentration in North China utilizing methane concentration products produced by the Google Earth Engine platform and the University of Bremen, Germany, based on the TROPOMI satellite data, and conducted a comparative analysis of the quality of the two datasets. The results demonstrate that the methane concentrations in North China exhibited an increasing trend from 2019 to 2023. Specifically, the Offline Methane data rose from 1850.25×10-9 to 1899.15 ×10-9, representing an increase of 48.90×10-9, while the Level 2XCH4 data rose from 1860.13 ×10-9 to 1909.60 ×10-9 with an increase of 49.47×10-9. The methane concentration was relatively high in Tianjin and Hebei Province, while that in the Inner Mongolia Autonomous Region was relatively low. The anomalously high methane concentrations were mainly distributed in Hebei and Shanxi provinces. A strong correlation between the two datasets was observed (r=0.92). Both datasets demonstrated a correlation greater than 0.85 with data from the Xianghe station, indicating that both datasets can effectively reflect the ground-level methane concentration. The Offline Methane data can provide visual downloads and high spatial resolution, but there are many data gaps. In practical applications, data fusion and other interpolation methods can be employed to fill these missing observations. The Level 2XCH4 data has lower spatial resolution but higher coverage, and can be processed by gridding based on the size of the study area, making it suitable for large-scale research.

methane(CH4)  /  temporal and spatial variations  /  TROPOMI product data  /  North China
李梦圆, 李军, 陈伟, 解北京, 张成业, 丁雅欣, 黄月军. 基于TROPOMI的华北地区CH4浓度时空变化与数据对比. 中国环境科学, 2025 , 45 (10) : 5378 -5389 .
Meng-yuan LI, Jun LI, Wei CHEN, Bei-jing XIE, Cheng-ye ZHANG, Ya-xin DING, Yue-Jun HUANG. Spatiotemporal variations and data comparison of CH4 concentrations in north China based on TROPOMI[J]. China Environmental Science, 2025 , 45 (10) : 5378 -5389 .
Year 2025 volume 45 Issue 10
72
21
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Article Info
  • Receive Date:2025-01-03
  • Online Date:2026-10-08
  • Published:2025-10-20
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  • Received:2025-01-03
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Affiliations
    1.Inner Mongolia Research Institute, China University of Mining and Technology-Beijing, Erdos 017010, China
    2.College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
    3.College of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
    4.Guoneng Beidian Shengli Energy Co., Ltd., Xilinhot 026000, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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