A measurement-driven cross-sectional method to assess the dynamics and flux of dust transport

During dust storms, dust particles are transported within a few kilometers above the ground. However, the dynamics and flux of dust transport at these altitudes are not fully understood. In this study, we employed a synergistic wind-particle profiling system in southern China to gather detailed vertical data on both aerosol characteristics and atmospheric dynamics during an unusually severe dust storm that transported from northern to southern China in April 2025. A measurement-driven cross-sectional method was developed to investigate the vertical distribution characteristics of transport dynamics and southward flux of dust, and to assess total amount of dust transported across the country. An intense spring cold front, combined with high dust emissions from the Gobi Desert, drove this southward transport. During the lower-level transport period, dust was primarily transported below 1.5 km, with a maximum southward flux density of 4.9 ± 2.9 g/m² at 775 m. The higher-level transport period exhibited a bimodal flux pattern. Additionally, the west-east distribution of dust concentration followed a Gaussian distribution. The total dust flux transported to southern China during the entire event was approximately 2.48 × 105 tons. Our cross-sectional approach supports quantitative investigations of the transport dynamics of various atmospheric components above the ground.

Authors

Institutions

Publication Details

Journal
npj natural hazards.
Published
2026-01-12
DOI
https://doi.org/10.1038/s44304-026-00166-y
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A measurement-driven cross-sectional method to assess the dynamics and flux of dust transport

Xingcheng Lu, Teng Yao, Changqing Lin, Tianshu Zhang et al.
npj natural hazards.
Atmospheric aerosols and clouds
article

A measurement-driven cross-sectional method to assess the dynamics and flux of dust transport

Xingcheng Lu, Teng Yao, Changqing Lin, Tianshu Zhang, Xuejiao Deng, Wenqing Liu, Jimmy C. H. Fung
article en

Abstract

During dust storms, dust particles are transported within a few kilometers above the ground. However, the dynamics and flux of dust transport at these altitudes are not fully understood. In this study, we employed a synergistic wind-particle profiling system in southern China to gather detailed vertical data on both aerosol characteristics and atmospheric dynamics during an unusually severe dust storm that transported from northern to southern China in April 2025. A measurement-driven cross-sectional method was developed to investigate the vertical distribution characteristics of transport dynamics and southward flux of dust, and to assess total amount of dust transported across the country. An intense spring cold front, combined with high dust emissions from the Gobi Desert, drove this southward transport. During the lower-level transport period, dust was primarily transported below 1.5 km, with a maximum southward flux density of 4.9 ± 2.9 g/m² at 775 m. The higher-level transport period exhibited a bimodal flux pattern. Additionally, the west-east distribution of dust concentration followed a Gaussian distribution. The total dust flux transported to southern China during the entire event was approximately 2.48 × 105 tons. Our cross-sectional approach supports quantitative investigations of the transport dynamics of various atmospheric components above the ground.

npj natural hazards.Vol. 3(1)
China Meteorological Administration (CN), Chinese University of Hong Kong (HK), Chinese Academy of Sciences (CN), Hong Kong University of Science and Technology (HK), Hefei Institutes of Physical Science (CN), Anhui Institute of Optics and Fine Mechanics (CN), National Science Centre (PL)
Hong Kong University of Science and Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences
Openalex Percentile: Top 94%
Atmospheric aerosols and clouds
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.