Abstract
This study analyzes ground-based observations and multi-source remote sensing data from eight dust storm events in 2024 at two sites: the Tazhong (TZ) station in the Taklamakan Desert interior and the Xiaotang (XT) station on its northern margin, systematically investigates the interrelationships among dust particle size, friction velocity (U*), and dust flux, and evaluates the applicability of remote sensing data in dust monitoring. The results indicate that particle size significantly influences both horizontal fluxes (Q) and vertical dust fluxes (F). Fine particles (d[0.5]) enhance surface dust flux, while coarse particles (D[4,3]—due to their greater gravitational settling—are less capable of sustained suspension, limiting their long-distance transport. A positive correlation exists between friction velocity (U*) and Q, whereas its impact on F is weaker, suggesting that vertical transport is regulated primarily by particle size, gravitational settling, and turbulent structures. Regarding remote sensing data, MODIS Aerosol Optical Depth (AOD) shows strong consistency with ground-based dust flux measurements, especially at the Xiaotang (XT) station, where AOD closely follows the variation trends of both Q and F. This reflects the effectiveness of remote sensing data in capturing changes in dust activity. Additionally, the Aerosol Absorbing Index (AAI) from Sentinel-5P exhibits a highly significant positive correlation with ground-level dust concentrations, effectively reflecting the vertical structure of dust events. This research provides valuable data support and theoretical foundation for dust warning systems and desertification control projects.
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Data availability
The MODIS aerosol optical depth (AOD) data used in this study were obtained from the NASA LAADS DAAC, and the Sentinel-5P aerosol absorbing index (AAI) data were provided by the ESA Copernicus Programme. These satellite datasets are publicly available.The ground-based dust horizontal transport flux (Q), vertical dust flux (F), multi-level wind, and meteorological observations were obtained from in situ field experiments conducted by the authors at the Taklamakan Desert Meteorological National Field Science Observation and Research Station. Due to the site-specific nature of the observation stations and the experimental characteristics of the datasets, these ground-based data are not publicly available but can be obtained from the corresponding authors upon reasonable request.
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Acknowledgements
This research was funded by the Tianshan Young Talents Program of Xinjiang (Project No. 2023TSYCCX0075), the China Meteorological Administration’s Young Innovative Team Project (Project No. CMA2024QN13), and the Tianshan Innovation Team Project of Xinjiang Science and Technology Innovation Team Program (Project No. 2022TSYCTD0007). We would like to thank the Desert Meteorological Institute of the China Meteorological Administration (Urumqi) for providing critical datasets. We also thank the School of Geography and Remote Sensing Science, Xinjiang University (Urumqi), for their technical support. Due to the station-specific nature of ground observation data, it is not publicly available but can be reasonably requested from the corresponding author. We appreciate the NASA LAADS DAAC data center (https://ladsweb.modaps.eosdis.nasa.gov) for providing MODIS data. We also thank the European Space Agency (ESA) Copernicus Program for providing Sentinel-5P data.
Funding
This research was funded by the Tianshan Talent Project of Xinjiang (Grant No. 2023TSYCCX0075), China Meteorological Administration Youth Innovation Team Project (CMA2024QN13); and the Xinjiang Science and Technology Innovation Team (Tianshan Innovation Team) Project (2022TSYCTD0007).
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M.M.: Conceptualization, writing—original draft, formal analysis. W.H.: Methodology, supervision, writing—review and editing. Y.L.: Validation. Y.W.: Investigation, data curation. F.Y.: Experimental design, supervision. C.Z., X.Y., A.M.: Investigation, data curation. M.M.: Visualization.
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Maihamuti, M., Huo, W., Liu, Y. et al. Study on the influence of key parameters of sand emission on dust flux based on multi-source data. Sci Rep (2026). https://doi.org/10.1038/s41598-026-45242-5
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DOI: https://doi.org/10.1038/s41598-026-45242-5
