Evidence map›Paper›PMID 41888203›Full record

ArticleScientific reports2026

Study on the influence of key parameters of sand emission on dust flux based on multi-source data.

Mayibaier Maihamuti, Wen Huo, Yongqiang Liu, Yifei Wang, Fan Yang, Chenglong Zhou, Xinghua Yang, Ali Mamtimin, Mierxiatijiang Maihemuti

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Mayibaier MaihamutiInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China.
Wen HuoInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China. huowenpet@idm.cn.
Yongqiang LiuInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China. liuyq@xju.edu.cn.
Yifei WangInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China.
Fan YangInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China.
Chenglong ZhouInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China.
Xinghua YangInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China.
Ali MamtiminInstitute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China.
Mierxiatijiang MaihemutiChina Merchants Xinjiang Quality and Standardization Research Institute Co., Ltd., Urumqi, 830011, China.

Funding

China Meteorological Administration Youth Innovation Team Project CMA2024QN13Tianshan Talent Project of Xinjiang 2023TSYCCX0075Xinjiang Science and Technology Innovation Team (Tianshan Innovation Team) Project 2022TSYCTD0007
6 · The paper itself

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.

Indexed as

Dust fluxDust monitoringFriction velocityMulti-source remote sensingParticle size

Identifiers

PMID41888203
PMCPMC13077078

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.