Observation-based quantification of aerosol transport using optical flow: A satellite perspective to characterize interregional transport of atmospheric pollution
Interregional transport plays a significant role in haze formation with varying and disputable contribution extent. Current research on quantitatively analyzing interregional atmospheric pollution transport has mainly relied on meteorological and chemical models. However, these models are typically affected by uncertainties due to the assumptions and simplifications inherent in the numerical simulations and source emission estimations. In this study, a comprehensive optical flow framework is developed to offer a new perspective on quantitative characterization of interregional transport of atmospheric pollution based on synergistic observations from geostationary and sun-synchronous satellites. In this framework, the high-frequency continuous aerosol observing images are regarded as video in computer vision, and an aerosol dynamic optical flow algorithm is proposed by incorporating aerosol-specific assumptions and constraints, overcoming the limitation that traditional optical flow methods are typically confined to rigid bodies. Results demonstrate that the developed optical flow framework could distinguish the aerosol transport process from other dynamic processes of aerosol development and accurately capture the fast-changing details of transport processes. Moreover, the satellite-based optical flow framework achieves aerosol transport results comparable to those of widely accepted model-based methods, demonstrating the physical interpretation of pixel-based optical flow results and highlighting its effectiveness in quantitative characterization of the atmospheric pollution transport process via the Aerosol Transport Index (ATI). Furthermore, a case analysis of long-term assessments of interregional transport of atmospheric pollution indicates that Beijing acts as a “sink” of atmospheric pollution, and a downward trend could be found from the annually averaged transported aerosol net loadings due to the emission reduction policy. Compared with model-based methods, the satellite-based optical flow framework is directly grounded in observations and does not rely on emission inventories that take years to update. Therefore, it not only helps improve understanding the patterns of atmospheric pollution interregional transport, but also provides a more efficient and economical way to assess the effectiveness of regional joint control policy. • First time to quantify aerosol transport process using satellite observations solely. • Regard high-frequency satellite aerosol observations as video in computer vision. • Propose ATI to provide physical interpretation for pixel-based optical flow results. • Optical flow method is more reliable and efficient comparing to model-based methods. • Beijing acts as a haze “sink”, yet net transported loadings show a downward trend.
Authors
- Yu Gu (ORCID: https://orcid.org/0000-0002-3412-0794)
- Bin Zhao (ORCID: https://orcid.org/0000-0003-1483-7680)
- Zhe Jiang (ORCID: https://orcid.org/0000-0002-0086-7486)
- Xing Chang (ORCID: https://orcid.org/0000-0002-7755-0751)
- Hongrong Shi (ORCID: https://orcid.org/0000-0002-5650-0077)
- Lunche Wang (ORCID: https://orcid.org/0000-0001-7783-5725)
- Wei Gong (ORCID: https://orcid.org/0000-0002-2276-8024)
- Tianhao Zhang (ORCID: https://orcid.org/0000-0003-3456-8262)
- Zhongmin Zhu (ORCID: https://orcid.org/0000-0003-3185-7050)
- Yun Lin (ORCID: https://orcid.org/0000-0001-8222-0346)
- Xinghui Xia
Institutions
- University of California, Los Angeles (US)
- Chinese Academy of Sciences (CN)
- China University of Geosciences (CN)
- Wuhan University (CN)
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN)
- Wuchang University of Technology (CN)
- Ministry of Transport (CN)
- State Key Joint Laboratory of Environment Simulation and Pollution Control (CN)
- Institute of Atmospheric Physics (CN)
- Wuchang Shouyi University
- Hubei University (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Remote Sensing of Environment
- Published
- 2024-10-03
- DOI
- https://doi.org/10.1016/j.rse.2024.114457
- Citations
- 4
- Primary Topic
- Atmospheric aerosols and clouds
- Type
- article
- Field-Weighted Citation Impact
- 1.13
Funders
- National Science Foundation
- National Natural Science Foundation of China