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Atmospheric pollutant transport pathway identification algorithm coupling optical flow vectors with movement distance constraints
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Wei-wen HE1, Bin ZOU1, *, Yong XU1, 2, Qin-ting ZHANG1, Jie XU3, Jian WU4
China Environmental Science | 2025, 45(9) : 4825 - 4836
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China Environmental Science | 2025, 45(9): 4825-4836
• Air Pollution Control •
Atmospheric pollutant transport pathway identification algorithm coupling optical flow vectors with movement distance constraints
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Wei-wen HE1, Bin ZOU1, *, Yong XU1, 2, Qin-ting ZHANG1, Jie XU3, Jian WU4
Affiliations
  • 1.School of Geosciences and Info-physics, Central South University, Changsha 410083, China
  • 2.School of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541006, China
  • 3.Changsha Municipal Ecological Environment Bureau Atmospheric Division, Changsha 410083, China
  • 4.Changsha Environmental Monitoring Center of Hunan Province, Changsha 410083, China
Published: 2025-09-20
Outline
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Proposing a novel algorithm for identifying atmospheric pollutant transport pathways by coupling optical flow vectors with movement distance constraints—Farneback-Distance Transmission Path Recognition Algorithm (FBD-TPRA). Based on high spatiotemporal-resolution (2km spatial resolution, 1h temporal resolution) PM2.5 concentration satellite remote sensing inversion data generated via a one-dimensional deep convolutional neural network (1D-CNN), this algorithm extracts inter-frame motion features of polluted air masses using optical flow and incorporates movement distance constraints to achieve continuous and refined reconstruction of pollutant transport pathways. Validation experiments conducted during three typical air pollution events in Changsha, Hunan Province (January 14, October 12, and October 27, 2024) demonstrate that the transport paths identified by the FBD-TPRA algorithm can reasonably explain the temporal relationships of urban concentration variations (Xiantao-Jingzhou-Yueyang-Changsha, Yueyang-Changde-Yiyang-Changsha, and Yueyang-Yiyang-Changsha). Compared with the widely used HYSPLIT model, the FBD-TPRA achieves strong consistency in net displacement direction(cosine similarity up to 0.99), but differ in path morphology, as reflected by dynamic time warping (DTW) values of 2.99°, 9.58°, and 3.69°, respectively. The study indicates that the FBD-TPRA algorithm enhances the characterization of pollutant transport processes by integrating high-resolution spatiotemporal pollutant concentration data and movement distance constraints, providing a new technical approach for identifying atmospheric pollution transport pathways.

PM2.5  /  atmospheric pollution  /  farneback optical flow  /  FBD-TPRA algorithm  /  HYSPLIT
贺威文, 邹滨, 徐勇, 张钦挺, 许杰, 吴坚. 耦合光流矢量与移动距离约束的大气污染传输路径识别算法. 中国环境科学, 2025 , 45 (9) : 4825 -4836 .
Wei-wen HE, Bin ZOU, Yong XU, Qin-ting ZHANG, Jie XU, Jian WU. Atmospheric pollutant transport pathway identification algorithm coupling optical flow vectors with movement distance constraints[J]. China Environmental Science, 2025 , 45 (9) : 4825 -4836 .
Year 2025 volume 45 Issue 9
70
17
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Article Info
  • Receive Date:2025-02-21
  • Online Date:2026-10-08
  • Published:2025-09-20
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  • Received:2025-02-21
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Affiliations
    1.School of Geosciences and Info-physics, Central South University, Changsha 410083, China
    2.School of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541006, China
    3.Changsha Municipal Ecological Environment Bureau Atmospheric Division, Changsha 410083, China
    4.Changsha Environmental Monitoring Center of Hunan Province, Changsha 410083, China
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